{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The effects of Brexit\n",
    "\n",
    "The aim of this notebook is to estimate the causal impact of Brexit upon the UK's GDP. This will be done using the {term}`synthetic control` approach. As such, it is similar to the policy brief \"What can we know about the cost of Brexit so far?\" {cite:p}`brexit2022policybrief` from the Center for European Reform. That approach did not use Bayesian estimation methods however.\n",
    "\n",
    "I did not use the GDP data from the above report however as it had been scaled in some way that was hard for me to understand how it related to the absolute GDP figures. Instead, GDP data was obtained courtesy of Prof. Dooruj Rambaccussing. Raw data is in units of trillions of USD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from pymc_extras.prior import Prior\n",
    "\n",
    "import causalpy as cp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "seed = 42"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Australia</th>\n",
       "      <th>Austria</th>\n",
       "      <th>Belgium</th>\n",
       "      <th>Canada</th>\n",
       "      <th>Denmark</th>\n",
       "      <th>Finland</th>\n",
       "      <th>France</th>\n",
       "      <th>Germany</th>\n",
       "      <th>Iceland</th>\n",
       "      <th>Luxemburg</th>\n",
       "      <th>Netherlands</th>\n",
       "      <th>New_Zealand</th>\n",
       "      <th>Norway</th>\n",
       "      <th>Sweden</th>\n",
       "      <th>Switzerland</th>\n",
       "      <th>UK</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>3.84048</td>\n",
       "      <td>0.802836</td>\n",
       "      <td>0.94117</td>\n",
       "      <td>16.93824</td>\n",
       "      <td>4.50096</td>\n",
       "      <td>0.51052</td>\n",
       "      <td>5.05450</td>\n",
       "      <td>6.63471</td>\n",
       "      <td>5.18157</td>\n",
       "      <td>0.114836</td>\n",
       "      <td>1.634391</td>\n",
       "      <td>0.47336</td>\n",
       "      <td>7.78753</td>\n",
       "      <td>10.32220</td>\n",
       "      <td>1.476532</td>\n",
       "      <td>4.61881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>3.86954</td>\n",
       "      <td>0.796545</td>\n",
       "      <td>0.94162</td>\n",
       "      <td>16.75340</td>\n",
       "      <td>4.41372</td>\n",
       "      <td>0.50829</td>\n",
       "      <td>5.05375</td>\n",
       "      <td>6.64530</td>\n",
       "      <td>5.16171</td>\n",
       "      <td>0.116259</td>\n",
       "      <td>1.634432</td>\n",
       "      <td>0.47916</td>\n",
       "      <td>7.71903</td>\n",
       "      <td>10.32867</td>\n",
       "      <td>1.485509</td>\n",
       "      <td>4.60431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>3.88115</td>\n",
       "      <td>0.799937</td>\n",
       "      <td>0.95352</td>\n",
       "      <td>16.82878</td>\n",
       "      <td>4.42898</td>\n",
       "      <td>0.51299</td>\n",
       "      <td>5.06237</td>\n",
       "      <td>6.68237</td>\n",
       "      <td>5.24132</td>\n",
       "      <td>0.118747</td>\n",
       "      <td>1.640982</td>\n",
       "      <td>0.48188</td>\n",
       "      <td>7.72400</td>\n",
       "      <td>10.32328</td>\n",
       "      <td>1.502506</td>\n",
       "      <td>4.60722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>3.91028</td>\n",
       "      <td>0.803823</td>\n",
       "      <td>0.96117</td>\n",
       "      <td>17.02503</td>\n",
       "      <td>4.43300</td>\n",
       "      <td>0.50903</td>\n",
       "      <td>5.09832</td>\n",
       "      <td>6.73155</td>\n",
       "      <td>5.22482</td>\n",
       "      <td>0.119302</td>\n",
       "      <td>1.650866</td>\n",
       "      <td>0.48805</td>\n",
       "      <td>7.72812</td>\n",
       "      <td>10.37107</td>\n",
       "      <td>1.515139</td>\n",
       "      <td>4.62152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.92716</td>\n",
       "      <td>0.800510</td>\n",
       "      <td>0.96615</td>\n",
       "      <td>17.23041</td>\n",
       "      <td>4.47128</td>\n",
       "      <td>0.51413</td>\n",
       "      <td>5.11625</td>\n",
       "      <td>6.78621</td>\n",
       "      <td>4.91128</td>\n",
       "      <td>0.121414</td>\n",
       "      <td>1.647748</td>\n",
       "      <td>0.49349</td>\n",
       "      <td>7.87891</td>\n",
       "      <td>10.64833</td>\n",
       "      <td>1.525864</td>\n",
       "      <td>4.65380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Australia   Austria  Belgium    Canada  Denmark  Finland   France  \\\n",
       "Time                                                                            \n",
       "2009-01-01    3.84048  0.802836  0.94117  16.93824  4.50096  0.51052  5.05450   \n",
       "2009-04-01    3.86954  0.796545  0.94162  16.75340  4.41372  0.50829  5.05375   \n",
       "2009-07-01    3.88115  0.799937  0.95352  16.82878  4.42898  0.51299  5.06237   \n",
       "2009-10-01    3.91028  0.803823  0.96117  17.02503  4.43300  0.50903  5.09832   \n",
       "2010-01-01    3.92716  0.800510  0.96615  17.23041  4.47128  0.51413  5.11625   \n",
       "\n",
       "            Germany  Iceland  Luxemburg  Netherlands  New_Zealand   Norway  \\\n",
       "Time                                                                         \n",
       "2009-01-01  6.63471  5.18157   0.114836     1.634391      0.47336  7.78753   \n",
       "2009-04-01  6.64530  5.16171   0.116259     1.634432      0.47916  7.71903   \n",
       "2009-07-01  6.68237  5.24132   0.118747     1.640982      0.48188  7.72400   \n",
       "2009-10-01  6.73155  5.22482   0.119302     1.650866      0.48805  7.72812   \n",
       "2010-01-01  6.78621  4.91128   0.121414     1.647748      0.49349  7.87891   \n",
       "\n",
       "              Sweden  Switzerland       UK  \n",
       "Time                                        \n",
       "2009-01-01  10.32220     1.476532  4.61881  \n",
       "2009-04-01  10.32867     1.485509  4.60431  \n",
       "2009-07-01  10.32328     1.502506  4.60722  \n",
       "2009-10-01  10.37107     1.515139  4.62152  \n",
       "2010-01-01  10.64833     1.525864  4.65380  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = (\n",
    "    cp.load_data(\"brexit\")\n",
    "    .assign(Time=lambda x: pd.to_datetime(x[\"Time\"]))\n",
    "    .set_index(\"Time\")\n",
    "    .loc[lambda x: x.index >= \"2009-01-01\"]\n",
    "    # manual exclusion of some countries\n",
    "    .drop([\"Japan\", \"Italy\", \"US\", \"Spain\", \"Portugal\"], axis=1)\n",
    ")\n",
    "\n",
    "# specify date of the Brexit vote announcement\n",
    "treatment_time = pd.to_datetime(\"2016 June 24\")\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get useful country lists\n",
    "target_country = \"UK\"\n",
    "all_countries = df.columns\n",
    "other_countries = all_countries.difference({target_country})\n",
    "all_countries = list(all_countries)\n",
    "other_countries = list(other_countries)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "az.style.use(\"arviz-white\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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jjz++r7nZwfZBBx2kL3/5y1q7dq3r8WAwqA0bNszba3zz5s0KhUL65Cc/qRNPPNH1mN2T+bOf/aze//7365vf/Kbz2LXXXqtNmzapUqlon3320Ze+9CUdeOCBnjn88R//sV7wghfoL//yL12B4zXXXDNvuL3XXnvpYx/7mF7zmtfM2ad7bGxMGzdu1MaNG3XbbbfpvPPOc9pf/OQnP9Edd9yho48+es5jDdPmzZtdrVzS6bS+8Y1vaP/99+/6/FQqpaOOOkpHHXWUzjzzTD3xxBOuyvpurrjiCtfFnGAwqIsuukh//ud/7nmuz+fToYceqkMPPVSve93rdNZZZzltUn71q1/pqquu0hlnnDHrsa6//nr9+Mc/do39xV/8hT7wgQ+4qsINw9B+++2nd7zjHXrta1/r3CEwzMpiW+dCkpJGtrDlMO2zzz5KJBKulj1PPfXU0I4382+A7Zhjjhna8QAAwPJDWxIAAIAlsH79ev3pn/6pa+zTn/70wFoi1Go1T0Xwi170Iv3zP/+zJ9ieKZ1O60tf+pL22Wcf1/ill17a9xzS6XTXYLtfF154oSfY7nTBBRcolUo527lcTnfeeadCoZAuu+wyT7A9Uzwe97Qi+fGPfzxvO5YXvOAF+vM///O+FqA87rjj9IEPfMA1ds011/T8+mG49957XdtvfOMbZw22u9lvv/304he/eNbHC4WCLrnkEtfYJz7xia7BdqdDDz1Ul1xyiatS+8orr5y1d7okff7zn3dt/9Ef/ZEuuuiiORfwfOYzn6nLL7+8r+9yMXbs2OHa9vv9SiQSS3LspWbfHWLrpZ/7Qvz0pz/1LNKZzWZXZbsXAAAwO8JtAACAJfLOd77TFdrdf//9+t73vjeQff/Xf/2Xcrmcsx0IBPShD31ozoDPlkwmPWHv3Xff3feikGefffaig+3169fr1FNPnfd5iURCxx9/vGf81FNP1fr16+d9/dFHH629997b2W42m3rggQf6m2yPTjrpJK1Zs8bZ/uUvfzmU4/Sqs0fxvvvuO9D9X3vtta6e5xs3bvRc2JnLEUcc4VqYcMeOHbrtttu6PvcXv/iFq9VNIBDQBz7wgZ56vB9wwAE6/fTTe57XYtg94W2rNdiWdv89mWnQi3aapqlvfvObOvvssz098M8444wlu2ABAACWB9qSAAAALJH9999fJ598sutW+s985jM68cQT5+0pPJ/OtgzHHntsX9W4Gzdu1L777utqn3D77bfrec97Xk+vDwaDOumkk3o+3mxOOeWUnp97+OGH67vf/e6CX3/YYYe5WiY88sgjXXsGL5bP59Phhx+uW265RZI0PT2tJ554Qvvtt9/Aj9WLzvDxnnvu0Rvf+MaB7f/GG290bb/5zW/uex+vetWr9J3vfMfZvuOOO/SKV7zC8zz7M7W95CUv0bOe9ayej3PqqafqC1/4wqwLhQ5KZ+V5NBrtex/HHHOM6wLWXE4++WR9/OMf7/sYgxCLxVzb3RYTncstt9ziaptjK5fLeuKJJ/STn/yka1uc5z3vefrrv/7r/iYLAABWPMJtAACAJXTOOefou9/9rhN2Pf744/rOd77TVyjbTWeV9ctf/vK+Xm8Yhl7xilfoiiuumHWfc1m/fr0ymUxfx+zmhS98Yc/P7Vw4LpPJ6DnPec6CX99Z0dwL0zT15JNP6ne/+51KpZLK5bJngTtJnkULn3rqqZGF2519z7/97W/r4IMP1qmnniqfb3E3dk5PT+uhhx5ytsPh8IL6ix966KGu7d/85jddn7d582bX9saNG/s6zrp163T44YcPve92MBh0bQ+6mnk5mVm1L2nOtkjdXHnllX0f84gjjtCll17a97EAAMDKR7gNAACwhPbaay+deuqpuuqqq5yxSy65RK973esWHMxMTU15+toedthhfe+n8zX9tOkY1OJ4M1uFzCcej7u2n/GMZ/TUjsLWWWHaGcrNptVq6X/+53/03//93/rFL36xoKCyWCz2/ZpBOfzww3XYYYfpnnvukSS12219+MMf1pe//GX96Z/+qf74j/9YRxxxxILOx82bN7v6yCeTSX3jG9/oez+dldSz9W2+//77XduHHHJI38c65JBDhh5ud56rMxdcXG0631skEhnasTKZjE477TSdddZZi777BQAArEz8PwAAAIAl9ra3vU3f/OY3nT68Tz/9tK699toF31LfrVVB5wKRvejsvVwoFGRZVk+B8SCqtiVvy4y5dFYZ99vHuLMfeS+tKX71q1/p//2//6eHH364r2N16jVIH5ZPfOITetOb3qR8Pu+Mbd26VV/84hf1xS9+UaFQSIcccoie//zn65hjjtExxxzTUyuNXbt2ebYvuuiiRc935jxtjUbDc2FhIef9Ql7Tr5k916XdFxRKpVJf5+wFF1ww66KnV155pR5//PHFTHFgOr+rxfbht0WjUSWTSa1du1aHH364jjrqKL385S+nxzYAAHs4wm0AAIAlNjY2ptNOO02f//znnbEvfOELOuWUUzzVxL3obKfh8/k8laK96Aza7ACul8B5IfPupp/K60G+thc//elPdfbZZ88aMPZj2D2e5/Oc5zxH3/zmN/X+979fd9xxh+fxRqOh3/zmN/rNb36jK664QrFYTC972ct05plnzrlgZ7cQehC6Vcd3O9ZCFmrs54LKQj3zmc/0jD344IN6/vOf3/M+Tj755Fkf+973vrcswu0nn3zSU7ndz90YkvTVr35VxxxzzCCnBQAAVrHFNdUDAADAgpx55plKp9PO9uTkpL761a+OcEbdDTswXilyuZz+/u//3hNsH3PMMXrPe96jq666SjfddJM2bdqku+++Ww888IDrn7mCyVF51rOepauvvlrXXHON3vCGN3h6kM9UqVR0ww036HWve53+6Z/+adZFAvtdPHA5mNlGZVgOPvhgz5jdFmY16eyBLknPfe5zRzATAACwp6ByGwAAYASSyaTOPPNMfepTn3LGvvzlL+tNb3qTUqlUX/vqfL5pmiqXy31XsXZWXPr9/gVVgK9GV111laanp53tVCqlz372s3rRi17U0+vtFjTL0VFHHaWjjjpKkrRlyxZt2rRJv/rVr7Rp0yY98sgjrudalqWrrrpKuVxO//Iv/+LZ18wLNpL04he/eEELBPai81jS7nN4bGysr/0sRf9ru4e5vZCsJG3atEmnnXba0I+9lH7xi194xp73vOeNYCYAAGBPQeU2AADAiLz5zW929eItFAq6/PLL+95Pt37XW7du7Xs/W7ZscW2nUikqt/9/P/zhD13b73vf+3oOtiW5gvHlbN9999VJJ52kD3/4w/re976nW265Reeff76y2azred/97nf185//3PP6zmD5ySefHNpcQ6GQpw/4Qs77hbymX9Fo1HO+3HrrrZqamhr6sZdKoVDQjTfe6BrbZ5999JznPGdEMwIAAHsCwm0AAIARiUajOuuss1xjV199tWdRvvmMjY15FqxbSMuDztfM1Vt5T9JqtVwLSAYCAb3qVa/q+fXtdlv33XffMKY2dPvss4/e9ra36cYbb/QsOHrDDTd4nt/ZgmLLli16+umnhza/znN0IZ/zUn03na1pGo2GrrvuuiU59lK49tprPXcovP71rx/RbAAAwJ6CcBsAAGCE3vjGN2qfffZxtiuVimuhyV513vrfWWk8H8uyPK+hncBu09PTrr7M2WxWkUik59ffcccdS9L6YpgmJiZ05plnusYeeOABz/Oe+cxnehZP/P73vz+0eR1xxBGu7Ztvvrmv12/fvl133333IKc0q5e//OWeCwSf//znhxr+L5V7771Xn/vc51xj0WhUb3zjG0c0IwAAsKcg3AYAABihUCiks88+2zX2n//5n30HXi996Utd2//7v/+rJ554oufX33rrrZ4WEscdd1xfc1itgsGga7tcLss0zZ5f/+Uvf3nQUxqJzmB2tj7iJ554omv78ssvV7lcHsqcjj/+eNf2T3/6U/3ud7/r+fXXXnttX9/lYgSDQZ1//vmusWKxqAsuuGBFLsRpe+KJJ/R3f/d3rn7i0u5FczvvKAEAABg0wm0AAIARO/nkk/XsZz/b2W40Gn0Hoq9+9atdvbdbrZYuuuiinoK7Uqmkj33sY66xww8/XEceeWRfc1it0um0q7dzpVLRHXfc0dNrv/Wtb+l///d/hzW1BWm1Wgt63aOPPurani24PP300xWLxZztXbt26YILLnBVvw/Ki170Iu2///7OdqvV0oc//OGejvXYY4/piiuuGPic5vLqV79aGzdudI394he/0Fvf+tYVWd3/wx/+UK9//es9/fqPPPJIve1tbxvRrAAAwJ6EcBsAAGDE/H6//u7v/s41tnPnzr72EYlEdMYZZ7jGfvrTn+of//Ef56wKLRQKeutb3+oJp97xjnf0dfzVzDAMvfCFL3SNffSjH1U+n5/zdd/5znf0wQ9+cJhTW5D3vve9+sAHPuDqIz6fLVu26Etf+pJr7Jhjjun63PHxcU8v+Ztuuklvf/vb+1pYs9Fo6Lvf/a5OPvnkWRdeNAzDE6L+5Cc/0Yc+9CG12+1Z9/3kk0/qjDPOUL1e73k+g/KJT3zCs8jiz372M/3Zn/2Zvv/97/d9EWDTpk193aWxWIVCQddff71OPvlknXPOOSoWi67HDzzwQF122WUKBAJLNicAALDn4v9xAAAALAN/8id/oi9+8Yv67W9/u+B9nHHGGbrtttt01113OWPXXXed7rnnHv3t3/6tjjvuOKVSKUnSjh079MMf/lCXXXaZJ0h/4xvf6Gn3sKf7i7/4C/34xz92th966CEn3Dv++OOVzWYl7W5Z8stf/lLXXHONfvKTn0iSwuGw1q9fr82bN49k7p2q1apuvPFG/ed//qcOOuggvexlL9ORRx6pgw8+WGvXrpVhGJKkZrOpRx55RD/60Y901VVXqVAoOPuIxWL6sz/7s1mPcdZZZ+m+++7TD37wA2fs1ltv1caNG/Xnf/7nOv7447V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",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 491,
       "width": 731
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the time series normalised so that intervention point (Q3 2016) is equal to 100\n",
    "gdp_at_intervention = df.loc[pd.to_datetime(\"2016 July 01\"), :]\n",
    "df_normalised = (df / gdp_at_intervention) * 100.0\n",
    "\n",
    "# plot\n",
    "fig, ax = plt.subplots()\n",
    "for col in other_countries:\n",
    "    ax.plot(df_normalised.index, df_normalised[col], color=\"grey\", alpha=0.2)\n",
    "\n",
    "ax.plot(df_normalised.index, df_normalised[target_country], color=\"red\", lw=3)\n",
    "# ax = df_normalised.plot(legend=False)\n",
    "\n",
    "# formatting\n",
    "ax.set(title=\"Normalised GDP\")\n",
    "ax.axvline(x=treatment_time, color=\"r\", ls=\":\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 611,
       "width": 689
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Examine how correlated the pre-intervention time series are\n",
    "\n",
    "pre_intervention_data = df.loc[df.index < treatment_time, :]\n",
    "\n",
    "corr = pre_intervention_data.corr()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "ax = sns.heatmap(\n",
    "    corr,\n",
    "    mask=np.triu(np.ones_like(corr, dtype=bool)),\n",
    "    cmap=sns.diverging_palette(230, 20, as_cmap=True),\n",
    "    vmin=-0.2,\n",
    "    vmax=1.0,\n",
    "    center=0,\n",
    "    square=True,\n",
    "    linewidths=0.5,\n",
    "    cbar_kws={\"shrink\": 0.8},\n",
    ")\n",
    "ax.set(title=\"Correlations for pre-intervention GDP data\");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the analysis\n",
    "\n",
    "Note: The analysis is (and should be) run on the raw GDP data. We do not use the normalised data shown above which was just for ease of visualization."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{note}\n",
    "The `random_seed` keyword argument for the PyMC sampler is not necessary. We use it here so that the results are reproducible.\n",
    ":::"
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   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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    {
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     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [beta, y_hat_sigma]\n"
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       "Output()"
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     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 70 seconds.\n",
      "There were 1 divergences after tuning. Increase `target_accept` or reparameterize.\n",
      "Chain 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "Sampling: [beta, y_hat, y_hat_sigma]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n"
     ]
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    "sample_kwargs = {\"tune\": 1000, \"target_accept\": 0.99, \"random_seed\": seed}\n",
    "\n",
    "result = cp.SyntheticControl(\n",
    "    df,\n",
    "    treatment_time,\n",
    "    control_units=other_countries,\n",
    "    treated_units=[target_country],\n",
    "    model=cp.pymc_models.WeightedSumFitter(\n",
    "        sample_kwargs=sample_kwargs,\n",
    "    ),\n",
    ")"
   ]
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   "source": [
    "While we are at it, let's plot the graphviz representation of the model. This shows us the inner workings of the `WeightedSumFitter` class which defines our synthetic control model with a sum to 1 constraint on the donor weights (here labelled as `coeffs`). This will be particularly useful when we come to exploring custom priors (see below)."
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   "cell_type": "code",
   "execution_count": 9,
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    "We currently get some divergences, but these are mostly dealt with by increasing `tune` and `target_accept` sampling parameters. Nevertheless, the sampling of this dataset/model combination feels a little brittle."
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       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 1MB\n",
       "Dimensions:        (chain: 4, draw: 1000, treated_units: 1, coeffs: 15,\n",
       "                    obs_ind: 30)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 32B 0 1 2 3\n",
       "  * draw           (draw) int64 8kB 0 1 2 3 4 5 6 ... 994 995 996 997 998 999\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "  * coeffs         (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Switzerland&#x27;\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "Data variables:\n",
       "    beta           (chain, draw, treated_units, coeffs) float64 480kB 0.2496 ...\n",
       "    y_hat_sigma    (chain, draw, treated_units) float64 32kB 0.02687 ... 0.03445\n",
       "    mu             (chain, draw, obs_ind, treated_units) float64 960kB 4.608 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:28.926299+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0\n",
       "    sampling_time:              69.69903612136841\n",
       "    tuning_steps:               1000</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-754e249c-ab2f-4a0e-9b32-5130649dcd3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-754e249c-ab2f-4a0e-9b32-5130649dcd3d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>treated_units</span>: 1</li><li><span class='xr-has-index'>coeffs</span>: 15</li><li><span class='xr-has-index'>obs_ind</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f371099f-e2c1-4aab-9f42-5e171624a566' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f371099f-e2c1-4aab-9f42-5e171624a566' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-a6be9bae-94d2-4240-958c-4f537f04f0be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6be9bae-94d2-4240-958c-4f537f04f0be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3752381d-7488-490f-99b9-5545f2a502a3' class='xr-var-data-in' type='checkbox'><label for='data-3752381d-7488-490f-99b9-5545f2a502a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-78073a2d-f2ad-48bb-a2b6-925d2fe6a8c5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78073a2d-f2ad-48bb-a2b6-925d2fe6a8c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a37277c5-4c83-4623-be26-4ece02ec7a23' class='xr-var-data-in' type='checkbox'><label for='data-a37277c5-4c83-4623-be26-4ece02ec7a23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-26579ea4-fa2a-42f3-a3c7-626a7e47902e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26579ea4-fa2a-42f3-a3c7-626a7e47902e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b76ce669-86c2-4263-bd69-0d0aa163a18f' class='xr-var-data-in' type='checkbox'><label for='data-b76ce669-86c2-4263-bd69-0d0aa163a18f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-3641f348-8f7e-4da2-ae48-c9eaff3e8a31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3641f348-8f7e-4da2-ae48-c9eaff3e8a31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec0dce56-7657-4bd6-8b8a-f32793a8a6af' class='xr-var-data-in' type='checkbox'><label for='data-ec0dce56-7657-4bd6-8b8a-f32793a8a6af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-a442d3b0-d874-4d98-8baa-900870201f4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a442d3b0-d874-4d98-8baa-900870201f4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4ffc27b-3b58-434d-bdae-f5acd5417e96' class='xr-var-data-in' type='checkbox'><label for='data-f4ffc27b-3b58-434d-bdae-f5acd5417e96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d07a6e6e-2388-4fc4-8094-f074ad90e3cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d07a6e6e-2388-4fc4-8094-f074ad90e3cd' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>beta</span></div><div class='xr-var-dims'>(chain, draw, treated_units, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2496 0.03484 ... 0.07178 0.2119</div><input id='attrs-008e4ff8-2a3e-46d4-a587-d61d2477a76e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-008e4ff8-2a3e-46d4-a587-d61d2477a76e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3ffe87c-e986-45da-9ee5-72dc2b07836d' class='xr-var-data-in' type='checkbox'><label for='data-d3ffe87c-e986-45da-9ee5-72dc2b07836d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0.24964953, 0.03483903, 0.01016717, ..., 0.13641841,\n",
       "          0.09281844, 0.07566757]],\n",
       "\n",
       "        [[0.1471535 , 0.01830209, 0.10707607, ..., 0.07083097,\n",
       "          0.12194576, 0.00783327]],\n",
       "\n",
       "        [[0.12698719, 0.01585318, 0.09649521, ..., 0.0746198 ,\n",
       "          0.1306532 , 0.01958531]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[0.03841868, 0.05856914, 0.00152453, ..., 0.03478133,\n",
       "          0.03979616, 0.11568492]],\n",
       "\n",
       "        [[0.06650663, 0.01460661, 0.04492623, ..., 0.02787876,\n",
       "          0.10140383, 0.0125553 ]],\n",
       "\n",
       "        [[0.01722413, 0.00807644, 0.01102455, ..., 0.15053799,\n",
       "          0.15680892, 0.21520378]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[0.03899732, 0.03705022, 0.12621402, ..., 0.05317504,\n",
       "          0.09748177, 0.02207708]],\n",
       "\n",
       "        [[0.05113643, 0.04802957, 0.16000673, ..., 0.00748662,\n",
       "          0.07975709, 0.07859915]],\n",
       "\n",
       "        [[0.09018508, 0.02982258, 0.1169135 , ..., 0.02991824,\n",
       "          0.08156609, 0.01382839]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[0.08214324, 0.1189921 , 0.03410813, ..., 0.16242809,\n",
       "          0.11413517, 0.10763267]],\n",
       "\n",
       "        [[0.15711145, 0.0543644 , 0.05692044, ..., 0.02746687,\n",
       "          0.08591104, 0.02761149]],\n",
       "\n",
       "        [[0.08530209, 0.02965823, 0.02182958, ..., 0.12929759,\n",
       "          0.07177903, 0.21192664]]]], shape=(4, 1000, 1, 15))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_hat_sigma</span></div><div class='xr-var-dims'>(chain, draw, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02687 0.02277 ... 0.03396 0.03445</div><input id='attrs-d8ba0dd5-1b0e-4a6f-9f7e-2c4234400994' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8ba0dd5-1b0e-4a6f-9f7e-2c4234400994' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ceee7b8-b322-4a66-8464-1b82d63c039c' class='xr-var-data-in' type='checkbox'><label for='data-8ceee7b8-b322-4a66-8464-1b82d63c039c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.02687173],\n",
       "        [0.02277067],\n",
       "        [0.02362927],\n",
       "        ...,\n",
       "        [0.04720551],\n",
       "        [0.03513527],\n",
       "        [0.0371926 ]],\n",
       "\n",
       "       [[0.02468617],\n",
       "        [0.02792236],\n",
       "        [0.02880851],\n",
       "        ...,\n",
       "        [0.03428762],\n",
       "        [0.02528695],\n",
       "        [0.03370745]],\n",
       "\n",
       "       [[0.0285582 ],\n",
       "        [0.03479421],\n",
       "        [0.03314989],\n",
       "        ...,\n",
       "        [0.03256654],\n",
       "        [0.03302409],\n",
       "        [0.03239989]],\n",
       "\n",
       "       [[0.03675442],\n",
       "        [0.02805192],\n",
       "        [0.02807599],\n",
       "        ...,\n",
       "        [0.03104989],\n",
       "        [0.03395763],\n",
       "        [0.03444788]]], shape=(4, 1000, 1))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.608 4.587 4.603 ... 5.243 5.31</div><input id='attrs-758b179a-32cd-4e7e-9135-dee13db3339a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-758b179a-32cd-4e7e-9135-dee13db3339a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ef4e93e-8988-42e1-826d-b67caa1682d5' class='xr-var-data-in' type='checkbox'><label for='data-2ef4e93e-8988-42e1-826d-b67caa1682d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[4.60846076],\n",
       "         [4.58732774],\n",
       "         [4.60268619],\n",
       "         ...,\n",
       "         [5.24784827],\n",
       "         [5.2564293 ],\n",
       "         [5.31400598]],\n",
       "\n",
       "        [[4.59870243],\n",
       "         [4.57648822],\n",
       "         [4.59616138],\n",
       "         ...,\n",
       "         [5.26442844],\n",
       "         [5.26013106],\n",
       "         [5.33250622]],\n",
       "\n",
       "        [[4.60796689],\n",
       "         [4.58529377],\n",
       "         [4.60414588],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [5.26189513],\n",
       "         [5.24693281],\n",
       "         [5.31152118]],\n",
       "\n",
       "        [[4.61937463],\n",
       "         [4.59653554],\n",
       "         [4.62298842],\n",
       "         ...,\n",
       "         [5.27667729],\n",
       "         [5.2616224 ],\n",
       "         [5.3603241 ]],\n",
       "\n",
       "        [[4.62798042],\n",
       "         [4.60271056],\n",
       "         [4.62571738],\n",
       "         ...,\n",
       "         [5.25100748],\n",
       "         [5.24342594],\n",
       "         [5.31045907]]]], shape=(4, 1000, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-69311dde-2417-404a-9845-4f5de61dead9' class='xr-section-summary-in' type='checkbox'  ><label for='section-69311dde-2417-404a-9845-4f5de61dead9' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e67657f3-f09a-48a9-9fb6-6595f3308f61' class='xr-index-data-in' type='checkbox'/><label for='index-e67657f3-f09a-48a9-9fb6-6595f3308f61' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-912e86f5-680b-4d8b-a05b-51b537cd144f' class='xr-index-data-in' type='checkbox'/><label for='index-912e86f5-680b-4d8b-a05b-51b537cd144f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>treated_units</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1f68c877-8f88-4e96-9be9-81b0159f7f20' class='xr-index-data-in' type='checkbox'/><label for='index-1f68c877-8f88-4e96-9be9-81b0159f7f20' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;UK&#x27;], dtype=&#x27;object&#x27;, name=&#x27;treated_units&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>coeffs</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b53eb33b-7f2c-4ccc-b179-82bf79938f05' class='xr-index-data-in' type='checkbox'/><label for='index-b53eb33b-7f2c-4ccc-b179-82bf79938f05' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;coeffs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e23d8704-5af3-4614-b604-8bfcef3246a0' class='xr-index-data-in' type='checkbox'/><label for='index-e23d8704-5af3-4614-b604-8bfcef3246a0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e0aba183-645f-465b-9a76-95d46d348198' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0aba183-645f-465b-9a76-95d46d348198' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:28.926299+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd><dt><span>sampling_time :</span></dt><dd>69.69903612136841</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_posterior_predictivee8c4559a-e15f-4322-a01a-8d110a8fb23a\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_posterior_predictivee8c4559a-e15f-4322-a01a-8d110a8fb23a\" class = \"xr-section-summary\">posterior_predictive</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1f1f1f;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 968kB\n",
       "Dimensions:        (chain: 4, draw: 1000, obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 32B 0 1 2 3\n",
       "  * draw           (draw) int64 8kB 0 1 2 3 4 5 6 ... 994 995 996 997 998 999\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (chain, draw, obs_ind, treated_units) float64 960kB 4.62 ....\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:29.143734+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-aeb61f9a-bfb5-4285-915c-4ea9e3b4f0f3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aeb61f9a-bfb5-4285-915c-4ea9e3b4f0f3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9f72fb24-86ed-4864-b68e-07a039aa94df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f72fb24-86ed-4864-b68e-07a039aa94df' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-bd130951-88b4-4845-b751-61c1304aa962' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd130951-88b4-4845-b751-61c1304aa962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c398aa89-b1fd-4e42-be50-116bc4b336bf' class='xr-var-data-in' type='checkbox'><label for='data-c398aa89-b1fd-4e42-be50-116bc4b336bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-ec81368b-8a2d-4bb0-aaad-0e81312a68c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec81368b-8a2d-4bb0-aaad-0e81312a68c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cffdf88-ed78-4234-9775-a6053ac57fe8' class='xr-var-data-in' type='checkbox'><label for='data-3cffdf88-ed78-4234-9775-a6053ac57fe8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-edf9e8a3-d2fa-4805-bc2a-b72f3bb34f34' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-edf9e8a3-d2fa-4805-bc2a-b72f3bb34f34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cd5e865-98d3-4c9d-a504-ff7cf986d4c1' class='xr-var-data-in' type='checkbox'><label for='data-7cd5e865-98d3-4c9d-a504-ff7cf986d4c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-5586a050-3e9f-4f11-8cd3-52b5e1fc7ef9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5586a050-3e9f-4f11-8cd3-52b5e1fc7ef9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-971ebe31-2397-4a6f-9f59-0f1fceff309e' class='xr-var-data-in' type='checkbox'><label for='data-971ebe31-2397-4a6f-9f59-0f1fceff309e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-43e0d012-19c9-4440-82b3-e06e42e495a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-43e0d012-19c9-4440-82b3-e06e42e495a6' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.62 4.604 4.603 ... 5.273 5.326</div><input id='attrs-73f03c6a-af53-47a7-bd9e-25a5b52e0332' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73f03c6a-af53-47a7-bd9e-25a5b52e0332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-192957be-d0dc-47af-a74e-fc738f596dd5' class='xr-var-data-in' type='checkbox'><label for='data-192957be-d0dc-47af-a74e-fc738f596dd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[4.61970201],\n",
       "         [4.60360062],\n",
       "         [4.60345977],\n",
       "         ...,\n",
       "         [5.25544394],\n",
       "         [5.22939768],\n",
       "         [5.31450343]],\n",
       "\n",
       "        [[4.57039485],\n",
       "         [4.63576884],\n",
       "         [4.59960868],\n",
       "         ...,\n",
       "         [5.29590041],\n",
       "         [5.27344571],\n",
       "         [5.32089887]],\n",
       "\n",
       "        [[4.61390571],\n",
       "         [4.59489239],\n",
       "         [4.62460026],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [5.26608884],\n",
       "         [5.19717247],\n",
       "         [5.32772629]],\n",
       "\n",
       "        [[4.59354559],\n",
       "         [4.57535888],\n",
       "         [4.6102472 ],\n",
       "         ...,\n",
       "         [5.21714256],\n",
       "         [5.1774473 ],\n",
       "         [5.32216061]],\n",
       "\n",
       "        [[4.63994779],\n",
       "         [4.60190922],\n",
       "         [4.66675624],\n",
       "         ...,\n",
       "         [5.26349995],\n",
       "         [5.27285699],\n",
       "         [5.32632389]]]], shape=(4, 1000, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-15b08d4f-08d7-4eb9-8c33-0d679affb64d' class='xr-section-summary-in' type='checkbox'  ><label for='section-15b08d4f-08d7-4eb9-8c33-0d679affb64d' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-71b2bdbf-04b5-4627-ae13-c7eeae6945c4' class='xr-index-data-in' type='checkbox'/><label for='index-71b2bdbf-04b5-4627-ae13-c7eeae6945c4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-60f7916a-f43b-4a81-83a9-04568cfc0c7d' class='xr-index-data-in' type='checkbox'/><label for='index-60f7916a-f43b-4a81-83a9-04568cfc0c7d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5c8f29fe-db34-4b4a-a79b-cc86f1973795' class='xr-index-data-in' type='checkbox'/><label for='index-5c8f29fe-db34-4b4a-a79b-cc86f1973795' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>treated_units</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7e0f7f3b-9201-48fd-8340-394d20d35bc4' class='xr-index-data-in' type='checkbox'/><label for='index-7e0f7f3b-9201-48fd-8340-394d20d35bc4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;UK&#x27;], dtype=&#x27;object&#x27;, name=&#x27;treated_units&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-48045602-6771-4784-9606-0fa87cc3ff71' class='xr-section-summary-in' type='checkbox'  checked><label for='section-48045602-6771-4784-9606-0fa87cc3ff71' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:29.143734+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_sample_statse2c59415-5291-4992-afca-c72ce1be065d\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_sample_statse2c59415-5291-4992-afca-c72ce1be065d\" class = \"xr-section-summary\">sample_stats</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
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       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
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       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1f1f1f;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 496kB\n",
       "Dimensions:                (chain: 4, draw: 1000)\n",
       "Coordinates:\n",
       "  * chain                  (chain) int64 32B 0 1 2 3\n",
       "  * draw                   (draw) int64 8kB 0 1 2 3 4 5 ... 995 996 997 998 999\n",
       "Data variables: (12/17)\n",
       "    acceptance_rate        (chain, draw) float64 32kB 0.9909 0.9988 ... 0.9941\n",
       "    step_size_bar          (chain, draw) float64 32kB 0.001979 ... 0.001812\n",
       "    step_size              (chain, draw) float64 32kB 0.00164 ... 0.002034\n",
       "    energy_error           (chain, draw) float64 32kB 0.02131 ... -0.08462\n",
       "    n_steps                (chain, draw) float64 32kB 1.023e+03 ... 1.023e+03\n",
       "    process_time_diff      (chain, draw) float64 32kB 0.03708 ... 0.03781\n",
       "    ...                     ...\n",
       "    perf_counter_diff      (chain, draw) float64 32kB 0.03715 ... 0.03786\n",
       "    diverging              (chain, draw) bool 4kB False False ... False False\n",
       "    largest_eigval         (chain, draw) float64 32kB nan nan nan ... nan nan\n",
       "    energy                 (chain, draw) float64 32kB -28.81 -25.42 ... -31.29\n",
       "    reached_max_treedepth  (chain, draw) bool 4kB True True True ... True False\n",
       "    lp                     (chain, draw) float64 32kB 32.78 39.79 ... 35.35\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:28.932843+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0\n",
       "    sampling_time:              69.69903612136841\n",
       "    tuning_steps:               1000</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b9d769c4-b97a-4ddd-8228-a5e2541657b8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b9d769c4-b97a-4ddd-8228-a5e2541657b8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6381b488-a7cc-4908-b7cc-c565c52cec25' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6381b488-a7cc-4908-b7cc-c565c52cec25' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-f5d3d10b-1964-4473-904e-7387d3a1d8c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5d3d10b-1964-4473-904e-7387d3a1d8c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d62cb72-dc77-4645-b6d3-76c88e63136a' class='xr-var-data-in' type='checkbox'><label for='data-8d62cb72-dc77-4645-b6d3-76c88e63136a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-6fba5850-f621-40aa-9b7d-ee543037c4b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6fba5850-f621-40aa-9b7d-ee543037c4b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8c9e27f-df33-4ff8-b15e-40e83470c028' class='xr-var-data-in' type='checkbox'><label for='data-a8c9e27f-df33-4ff8-b15e-40e83470c028' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b42a4b5a-779f-49e1-bd0e-d1e9ff96a2dd' class='xr-section-summary-in' type='checkbox'  ><label for='section-b42a4b5a-779f-49e1-bd0e-d1e9ff96a2dd' class='xr-section-summary' >Data variables: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acceptance_rate</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9909 0.9988 ... 0.9813 0.9941</div><input id='attrs-53cbf741-69a7-426e-85f8-58eeeb6837e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53cbf741-69a7-426e-85f8-58eeeb6837e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92a14daf-46c6-4189-bd34-e3b137addcd1' class='xr-var-data-in' type='checkbox'><label for='data-92a14daf-46c6-4189-bd34-e3b137addcd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.99086837, 0.99882357, 0.98538415, ..., 0.98122484, 0.99778679,\n",
       "        0.99723396],\n",
       "       [0.98992801, 0.98297498, 0.99894204, ..., 0.99978495, 0.98852646,\n",
       "        0.9694623 ],\n",
       "       [0.98854545, 0.99176879, 0.99927103, ..., 0.9977    , 0.99626108,\n",
       "        0.99099907],\n",
       "       [0.99927957, 0.99522932, 0.99581267, ..., 0.99958952, 0.98132188,\n",
       "        0.99407097]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size_bar</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001979 0.001979 ... 0.001812</div><input id='attrs-b6d128a6-822b-4b34-9a50-1165485b5af7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6d128a6-822b-4b34-9a50-1165485b5af7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c70ee77-ce1a-4c9a-ab38-c6ae4acd967e' class='xr-var-data-in' type='checkbox'><label for='data-5c70ee77-ce1a-4c9a-ab38-c6ae4acd967e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00197915, 0.00197915, 0.00197915, ..., 0.00197915, 0.00197915,\n",
       "        0.00197915],\n",
       "       [0.00194233, 0.00194233, 0.00194233, ..., 0.00194233, 0.00194233,\n",
       "        0.00194233],\n",
       "       [0.00189668, 0.00189668, 0.00189668, ..., 0.00189668, 0.00189668,\n",
       "        0.00189668],\n",
       "       [0.00181165, 0.00181165, 0.00181165, ..., 0.00181165, 0.00181165,\n",
       "        0.00181165]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00164 0.00164 ... 0.002034</div><input id='attrs-c8cca90a-1028-4d0e-abc9-909c9b950553' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8cca90a-1028-4d0e-abc9-909c9b950553' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10d90c0b-7e00-401d-a102-e39fce879635' class='xr-var-data-in' type='checkbox'><label for='data-10d90c0b-7e00-401d-a102-e39fce879635' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00164014, 0.00164014, 0.00164014, ..., 0.00164014, 0.00164014,\n",
       "        0.00164014],\n",
       "       [0.00188633, 0.00188633, 0.00188633, ..., 0.00188633, 0.00188633,\n",
       "        0.00188633],\n",
       "       [0.00192616, 0.00192616, 0.00192616, ..., 0.00192616, 0.00192616,\n",
       "        0.00192616],\n",
       "       [0.00203402, 0.00203402, 0.00203402, ..., 0.00203402, 0.00203402,\n",
       "        0.00203402]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02131 -0.003949 ... -0.08462</div><input id='attrs-b64ba697-0721-4c81-8397-6a9f20f2ed26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b64ba697-0721-4c81-8397-6a9f20f2ed26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feeaeae1-6e60-4873-9a61-0e99077f17f5' class='xr-var-data-in' type='checkbox'><label for='data-feeaeae1-6e60-4873-9a61-0e99077f17f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 2.13093387e-02, -3.94916687e-03,  3.54395248e-02, ...,\n",
       "         2.26870935e-02, -2.29604863e-03, -1.81683009e-02],\n",
       "       [ 6.24032488e-03,  1.93217234e-02, -2.94682756e-02, ...,\n",
       "         1.47672801e-05,  3.78013300e-02,  2.94985626e-02],\n",
       "       [ 4.52635495e-02, -1.44761084e-02, -9.65669105e-03, ...,\n",
       "        -1.06729194e-02, -1.86880151e-02, -3.46026586e-04],\n",
       "       [-2.08086611e-02, -1.51914219e-02,  1.75065472e-03, ...,\n",
       "         5.92410270e-04,  2.08973429e-02, -8.46206469e-02]],\n",
       "      shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_steps</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-58951577-96d7-4fe0-8987-82fb16f5a1f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58951577-96d7-4fe0-8987-82fb16f5a1f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35c70f41-d26d-498b-bbdd-cfca68a969dd' class='xr-var-data-in' type='checkbox'><label for='data-35c70f41-d26d-498b-bbdd-cfca68a969dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>process_time_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03708 0.03851 ... 0.03793 0.03781</div><input id='attrs-c6f1eeed-c4dc-47db-ab81-1e2ed2d7ff94' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6f1eeed-c4dc-47db-ab81-1e2ed2d7ff94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c22e0ba-474d-4649-ba23-0d29f74d6c9f' class='xr-var-data-in' type='checkbox'><label for='data-8c22e0ba-474d-4649-ba23-0d29f74d6c9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.037082, 0.038512, 0.038291, ..., 0.035695, 0.035609, 0.033551],\n",
       "       [0.037082, 0.03815 , 0.037432, ..., 0.037293, 0.036091, 0.032045],\n",
       "       [0.036466, 0.036972, 0.03675 , ..., 0.038528, 0.03923 , 0.045157],\n",
       "       [0.046545, 0.03831 , 0.039513, ..., 0.039791, 0.037927, 0.037806]],\n",
       "      shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_start</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.231e+04 1.231e+04 ... 1.235e+04</div><input id='attrs-a4d001ac-66f9-44bc-8247-3c667781db71' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4d001ac-66f9-44bc-8247-3c667781db71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5241047a-2e6a-4839-b28d-69a347542378' class='xr-var-data-in' type='checkbox'><label for='data-5241047a-2e6a-4839-b28d-69a347542378' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[12313.9834425 , 12314.02065004, 12314.05966925, ...,\n",
       "        12352.66399279, 12352.699809  , 12352.73578904],\n",
       "       [12313.97352538, 12314.01071171, 12314.04925754, ...,\n",
       "        12352.66237792, 12352.69978946, 12352.73622412],\n",
       "       [12313.95695679, 12313.99355767, 12314.03066421, ...,\n",
       "        12352.51957562, 12352.55825725, 12352.59758513],\n",
       "       [12313.90037633, 12313.95411975, 12313.99325762, ...,\n",
       "        12352.48602133, 12352.52618958, 12352.56424117]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03267 -0.1543 ... 0.05913 -0.1361</div><input id='attrs-b0b10ae7-4a87-4acf-a405-2ebae65d45c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0b10ae7-4a87-4acf-a405-2ebae65d45c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-829f29e2-c7b0-43ce-95cb-650037832aea' class='xr-var-data-in' type='checkbox'><label for='data-829f29e2-c7b0-43ce-95cb-650037832aea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.03266648, -0.15425651, -0.12740746, ...,  0.05457645,\n",
       "        -0.07075316, -0.10715167],\n",
       "       [-0.08280064, -0.12434703, -0.03416169, ..., -0.00637034,\n",
       "        -0.34002809,  0.11382564],\n",
       "       [-0.26020771, -0.29440736, -0.07435699, ..., -0.09377657,\n",
       "        -0.22379783, -0.24246568],\n",
       "       [-0.09119369, -0.02183932, -0.01614251, ..., -0.00280421,\n",
       "         0.05913082, -0.13609552]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smallest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c918657a-e371-4bab-9316-85ce2db883ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c918657a-e371-4bab-9316-85ce2db883ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7f049d8-6edc-4cc2-90d9-a1ab562821c7' class='xr-var-data-in' type='checkbox'><label for='data-d7f049d8-6edc-4cc2-90d9-a1ab562821c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>index_in_trajectory</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>718 666 118 616 ... -523 727 -505</div><input id='attrs-22b56a7c-95e9-4181-8d28-17823b21d3ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22b56a7c-95e9-4181-8d28-17823b21d3ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47e4c9f2-4268-4734-b204-f5f240ee4390' class='xr-var-data-in' type='checkbox'><label for='data-47e4c9f2-4268-4734-b204-f5f240ee4390' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 718,  666,  118, ...,  226,  764, -483],\n",
       "       [ 202,  495, -577, ..., -434, -680,  640],\n",
       "       [ 541,  408, -186, ...,  530, -688, -772],\n",
       "       [-398, -586, -342, ..., -523,  727, -505]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tree_depth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10 10 10 10 10 ... 10 10 10 10 10</div><input id='attrs-8f832a6d-680f-452e-91e3-86e7e227cb73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f832a6d-680f-452e-91e3-86e7e227cb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1346641a-dd5f-47e8-b71f-4a96627003ae' class='xr-var-data-in' type='checkbox'><label for='data-1346641a-dd5f-47e8-b71f-4a96627003ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03715 0.03896 ... 0.038 0.03786</div><input id='attrs-4102138d-065b-43a8-8eb7-8e8ae8fdd6d2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4102138d-065b-43a8-8eb7-8e8ae8fdd6d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-353f02a4-d747-4c98-9683-e35d9f94882c' class='xr-var-data-in' type='checkbox'><label for='data-353f02a4-d747-4c98-9683-e35d9f94882c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.03714575, 0.03895788, 0.03836792, ..., 0.03576508, 0.03591267,\n",
       "        0.03362146],\n",
       "       [0.03713408, 0.03848292, 0.03751425, ..., 0.03735054, 0.03637254,\n",
       "        0.03209442],\n",
       "       [0.03653767, 0.03705642, 0.03706175, ..., 0.03863475, 0.03928021,\n",
       "        0.04997437],\n",
       "       [0.05355933, 0.03906092, 0.03961954, ..., 0.04011575, 0.03800483,\n",
       "        0.03786067]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diverging</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-235f6eed-42b9-437d-9088-233a81523da4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-235f6eed-42b9-437d-9088-233a81523da4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47f6b913-9dba-42a6-a53e-c6f04be1ba34' class='xr-var-data-in' type='checkbox'><label for='data-47f6b913-9dba-42a6-a53e-c6f04be1ba34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>largest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-19173f87-7048-423d-9320-fcd726d958f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19173f87-7048-423d-9320-fcd726d958f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9543ae8d-5946-44ae-a4db-e9654a7b4dba' class='xr-var-data-in' type='checkbox'><label for='data-9543ae8d-5946-44ae-a4db-e9654a7b4dba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-28.81 -25.42 ... -28.12 -31.29</div><input id='attrs-426bd49f-afb9-4ea6-98e3-9e86b563ee75' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-426bd49f-afb9-4ea6-98e3-9e86b563ee75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d89277e-9f8c-4e86-9025-a9b39173295c' class='xr-var-data-in' type='checkbox'><label for='data-9d89277e-9f8c-4e86-9025-a9b39173295c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-28.80629369, -25.42404915, -33.73610485, ..., -24.46701371,\n",
       "        -26.12720828, -28.3080102 ],\n",
       "       [-37.31087064, -39.07674631, -38.79859145, ..., -35.1735943 ,\n",
       "        -23.31758944, -26.11559932],\n",
       "       [-32.15334662, -31.80873375, -30.05996691, ..., -32.01062409,\n",
       "        -33.19118936, -34.05287501],\n",
       "       [-26.97644633, -31.77878937, -34.8958783 , ..., -26.89978463,\n",
       "        -28.12438538, -31.2879477 ]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>reached_max_treedepth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... True True False</div><input id='attrs-1fd63faf-bc73-4bb3-9a0c-56c56342b90c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1fd63faf-bc73-4bb3-9a0c-56c56342b90c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d8b4580-4036-482c-8967-552af44873e5' class='xr-var-data-in' type='checkbox'><label for='data-4d8b4580-4036-482c-8967-552af44873e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True, False,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True, False]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lp</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.78 39.79 38.94 ... 37.35 35.35</div><input id='attrs-f194a8d8-8513-4a23-b4a0-9581c76eec5b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f194a8d8-8513-4a23-b4a0-9581c76eec5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d784a8c5-a0a7-400b-b5a1-7c238f17b8c1' class='xr-var-data-in' type='checkbox'><label for='data-d784a8c5-a0a7-400b-b5a1-7c238f17b8c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[32.78309132, 39.78780282, 38.94039048, ..., 33.16248801,\n",
       "        40.30207775, 36.60630113],\n",
       "       [42.46721787, 42.94117762, 41.80417224, ..., 41.11589702,\n",
       "        34.02738911, 40.47110987],\n",
       "       [40.90354096, 40.03080474, 40.74533567, ..., 39.54501264,\n",
       "        38.19923816, 39.09112538],\n",
       "       [37.95289205, 40.04948618, 40.92364137, ..., 34.38964863,\n",
       "        37.35102582, 35.35062255]], shape=(4, 1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2e8e7d1-35a2-4589-8e7f-074499429536' class='xr-section-summary-in' type='checkbox'  ><label for='section-a2e8e7d1-35a2-4589-8e7f-074499429536' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fa982f04-4374-4bbc-9a8e-fd59bdee4942' class='xr-index-data-in' type='checkbox'/><label for='index-fa982f04-4374-4bbc-9a8e-fd59bdee4942' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-ae6e1c23-c2e6-432a-be61-60f3035c9efa' class='xr-index-data-in' type='checkbox'/><label for='index-ae6e1c23-c2e6-432a-be61-60f3035c9efa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-19f337cd-c7d8-4269-ba54-ba43303e77b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-19f337cd-c7d8-4269-ba54-ba43303e77b1' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:28.932843+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd><dt><span>sampling_time :</span></dt><dd>69.69903612136841</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_prior50ce498d-77b0-42a2-bbeb-30ec8f1cb9f4\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_prior50ce498d-77b0-42a2-bbeb-30ec8f1cb9f4\" class = \"xr-section-summary\">prior</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 189kB\n",
       "Dimensions:        (chain: 1, draw: 500, treated_units: 1, coeffs: 15,\n",
       "                    obs_ind: 30)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 8B 0\n",
       "  * draw           (draw) int64 4kB 0 1 2 3 4 5 6 ... 494 495 496 497 498 499\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "  * coeffs         (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Switzerland&#x27;\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "Data variables:\n",
       "    y_hat_sigma    (chain, draw, treated_units) float64 4kB 0.4183 ... 0.9914\n",
       "    beta           (chain, draw, treated_units, coeffs) float64 60kB 0.01287 ...\n",
       "    mu             (chain, draw, obs_ind, treated_units) float64 120kB 5.228 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:29.063859+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e0eefb73-254e-4d03-bde5-b56831f4d44a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e0eefb73-254e-4d03-bde5-b56831f4d44a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 1</li><li><span class='xr-has-index'>draw</span>: 500</li><li><span class='xr-has-index'>treated_units</span>: 1</li><li><span class='xr-has-index'>coeffs</span>: 15</li><li><span class='xr-has-index'>obs_ind</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9365201c-85e1-4caf-8c53-e71f725e343b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9365201c-85e1-4caf-8c53-e71f725e343b' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-359f7a39-f240-4554-bc0b-86a6e1032a50' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-359f7a39-f240-4554-bc0b-86a6e1032a50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d20d7f24-e2a1-4697-86cf-562e972ee46c' class='xr-var-data-in' type='checkbox'><label for='data-d20d7f24-e2a1-4697-86cf-562e972ee46c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 495 496 497 498 499</div><input id='attrs-de012f9b-a546-4730-b3dd-0a2f7d5dd38b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de012f9b-a546-4730-b3dd-0a2f7d5dd38b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be852317-2180-402b-98bd-d7ba626ecd7a' class='xr-var-data-in' type='checkbox'><label for='data-be852317-2180-402b-98bd-d7ba626ecd7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 497, 498, 499], shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-f5aea848-25ab-41aa-b48c-7a8b07473d6f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5aea848-25ab-41aa-b48c-7a8b07473d6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3e984c1-9908-4871-bd97-598302338ece' class='xr-var-data-in' type='checkbox'><label for='data-d3e984c1-9908-4871-bd97-598302338ece' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-17ffa1cb-22c4-47d7-8657-76e61c094f28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17ffa1cb-22c4-47d7-8657-76e61c094f28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bced261b-cba3-4dcd-9fcd-0d6521763870' class='xr-var-data-in' type='checkbox'><label for='data-bced261b-cba3-4dcd-9fcd-0d6521763870' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-499f9460-52ef-4bed-ba89-e6be5937f1a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-499f9460-52ef-4bed-ba89-e6be5937f1a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-204ce1ad-5e63-46e0-b3d2-5d698b65f30b' class='xr-var-data-in' type='checkbox'><label for='data-204ce1ad-5e63-46e0-b3d2-5d698b65f30b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5870996b-d2ed-4d53-8d76-04e273958a57' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5870996b-d2ed-4d53-8d76-04e273958a57' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat_sigma</span></div><div class='xr-var-dims'>(chain, draw, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4183 0.6056 ... 0.9556 0.9914</div><input id='attrs-08174f65-0286-4116-9333-3dd0de9d4c57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08174f65-0286-4116-9333-3dd0de9d4c57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03c4c566-75dd-49fc-8826-d462401cdd7e' class='xr-var-data-in' type='checkbox'><label for='data-03c4c566-75dd-49fc-8826-d462401cdd7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.41832997],\n",
       "        [0.60557617],\n",
       "        [0.02878786],\n",
       "        [1.084246  ],\n",
       "        [1.46422098],\n",
       "        [0.29072736],\n",
       "        [1.33075642],\n",
       "        [0.03472346],\n",
       "        [0.28041847],\n",
       "        [0.10749307],\n",
       "        [1.92080086],\n",
       "        [1.57864499],\n",
       "        [1.00595719],\n",
       "        [0.45121505],\n",
       "        [0.59343367],\n",
       "        [0.09382112],\n",
       "        [1.85195867],\n",
       "        [0.25590475],\n",
       "        [0.28298637],\n",
       "        [0.415816  ],\n",
       "...\n",
       "        [0.00701465],\n",
       "        [1.35254573],\n",
       "        [0.55302397],\n",
       "        [1.00111538],\n",
       "        [0.4508672 ],\n",
       "        [0.6071619 ],\n",
       "        [1.72811239],\n",
       "        [0.38531025],\n",
       "        [1.0977206 ],\n",
       "        [1.21844911],\n",
       "        [1.0680861 ],\n",
       "        [0.81158037],\n",
       "        [0.88338946],\n",
       "        [0.61570669],\n",
       "        [0.07811817],\n",
       "        [0.42106163],\n",
       "        [1.15124221],\n",
       "        [0.64150838],\n",
       "        [0.95555201],\n",
       "        [0.99141828]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beta</span></div><div class='xr-var-dims'>(chain, draw, treated_units, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.01287 0.02406 ... 0.07148 0.1187</div><input id='attrs-8e747015-9f36-4dd1-9d65-02fed6faf49a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e747015-9f36-4dd1-9d65-02fed6faf49a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a91e719d-ac75-4642-9980-c5ac7e5cc93f' class='xr-var-data-in' type='checkbox'><label for='data-a91e719d-ac75-4642-9980-c5ac7e5cc93f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[1.28673019e-02, 2.40590691e-02, 8.81535474e-03, ...,\n",
       "          2.46062988e-01, 1.31710227e-02, 1.54113717e-01]],\n",
       "\n",
       "        [[2.06274725e-01, 4.16856090e-02, 1.58191866e-02, ...,\n",
       "          2.58501881e-02, 7.86743512e-02, 3.98640345e-02]],\n",
       "\n",
       "        [[6.00244931e-02, 5.34500947e-02, 7.57567030e-02, ...,\n",
       "          3.67472899e-03, 6.22890619e-02, 1.44055379e-01]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[9.57669162e-04, 2.08602266e-01, 8.96706706e-02, ...,\n",
       "          1.36173877e-04, 1.28634900e-01, 4.41735520e-02]],\n",
       "\n",
       "        [[9.99641177e-02, 2.66011054e-01, 3.69254414e-02, ...,\n",
       "          1.68997859e-01, 3.86290787e-02, 3.73123402e-03]],\n",
       "\n",
       "        [[1.09383888e-01, 3.85367885e-02, 2.97928720e-02, ...,\n",
       "          2.11351766e-02, 7.14798269e-02, 1.18669439e-01]]]],\n",
       "      shape=(1, 500, 1, 15))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.228 5.19 5.21 ... 7.134 7.139</div><input id='attrs-c744d5c4-c413-49d2-9ecf-2324e401aa55' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c744d5c4-c413-49d2-9ecf-2324e401aa55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58790c12-7a2d-4242-9fa4-f3956697f2e7' class='xr-var-data-in' type='checkbox'><label for='data-58790c12-7a2d-4242-9fa4-f3956697f2e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[5.22812388],\n",
       "         [5.18957389],\n",
       "         [5.21010906],\n",
       "         ...,\n",
       "         [5.83835914],\n",
       "         [5.84804287],\n",
       "         [5.87400261]],\n",
       "\n",
       "        [[4.24449492],\n",
       "         [4.23210444],\n",
       "         [4.25160337],\n",
       "         ...,\n",
       "         [4.87256063],\n",
       "         [4.88028663],\n",
       "         [4.945048  ]],\n",
       "\n",
       "        [[4.95677392],\n",
       "         [4.93122453],\n",
       "         [4.95750211],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [3.37579416],\n",
       "         [3.38558929],\n",
       "         [3.39770012]],\n",
       "\n",
       "        [[3.78606753],\n",
       "         [3.76418438],\n",
       "         [3.77808849],\n",
       "         ...,\n",
       "         [4.27239669],\n",
       "         [4.27550378],\n",
       "         [4.30812397]],\n",
       "\n",
       "        [[6.19248441],\n",
       "         [6.16187203],\n",
       "         [6.18703184],\n",
       "         ...,\n",
       "         [7.09438275],\n",
       "         [7.13352076],\n",
       "         [7.13871076]]]], shape=(1, 500, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33007ad2-d962-453a-8662-5503b39c8ff7' class='xr-section-summary-in' type='checkbox'  ><label for='section-33007ad2-d962-453a-8662-5503b39c8ff7' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-51422ac3-3d6f-436b-8b71-2fbb4115ff20' class='xr-index-data-in' type='checkbox'/><label for='index-51422ac3-3d6f-436b-8b71-2fbb4115ff20' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d305aef4-5ba7-4955-adc9-150a61869072' class='xr-index-data-in' type='checkbox'/><label for='index-d305aef4-5ba7-4955-adc9-150a61869072' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       490, 491, 492, 493, 494, 495, 496, 497, 498, 499],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>treated_units</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b6b0eb16-ee07-4064-a261-05fe757705ac' class='xr-index-data-in' type='checkbox'/><label for='index-b6b0eb16-ee07-4064-a261-05fe757705ac' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;UK&#x27;], dtype=&#x27;object&#x27;, name=&#x27;treated_units&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>coeffs</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-205fdfa5-57b7-4c86-8899-d6259e89d01a' class='xr-index-data-in' type='checkbox'/><label for='index-205fdfa5-57b7-4c86-8899-d6259e89d01a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;coeffs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3f89981f-70d8-4bd8-9915-578bea75d59c' class='xr-index-data-in' type='checkbox'/><label for='index-3f89981f-70d8-4bd8-9915-578bea75d59c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06ff29b6-084d-4704-957b-f68c373b112e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06ff29b6-084d-4704-957b-f68c373b112e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:29.063859+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_prior_predictivee17e5d02-c603-4235-bfa9-bc76ccf5b458\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_prior_predictivee17e5d02-c603-4235-bfa9-bc76ccf5b458\" class = \"xr-section-summary\">prior_predictive</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1f1f1f;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 124kB\n",
       "Dimensions:        (chain: 1, draw: 500, obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 8B 0\n",
       "  * draw           (draw) int64 4kB 0 1 2 3 4 5 6 ... 494 495 496 497 498 499\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (chain, draw, obs_ind, treated_units) float64 120kB 5.753 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:29.065707+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2b2e669d-aab9-4f62-997c-2e9cec2b3a9a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2b2e669d-aab9-4f62-997c-2e9cec2b3a9a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 1</li><li><span class='xr-has-index'>draw</span>: 500</li><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8e7593f6-6433-4868-b3e9-d31b892c764e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8e7593f6-6433-4868-b3e9-d31b892c764e' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-7232a172-f599-43aa-a19a-0f4c8bbbf2ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7232a172-f599-43aa-a19a-0f4c8bbbf2ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15d76931-a1bc-461f-a590-54d9b4d7f89f' class='xr-var-data-in' type='checkbox'><label for='data-15d76931-a1bc-461f-a590-54d9b4d7f89f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 495 496 497 498 499</div><input id='attrs-350e2267-baf4-4558-b123-5945bc9f9d8b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-350e2267-baf4-4558-b123-5945bc9f9d8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-020f4e6a-951c-4cfd-90c2-b24b2d42551f' class='xr-var-data-in' type='checkbox'><label for='data-020f4e6a-951c-4cfd-90c2-b24b2d42551f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 497, 498, 499], shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-8efd7d94-03ed-405d-bf9e-8021c82b84b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8efd7d94-03ed-405d-bf9e-8021c82b84b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b761d540-9f9b-46f6-8650-62f5b224f512' class='xr-var-data-in' type='checkbox'><label for='data-b761d540-9f9b-46f6-8650-62f5b224f512' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-fba1d9d3-35c8-4b3e-accb-30fcedfb8235' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fba1d9d3-35c8-4b3e-accb-30fcedfb8235' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aa972f4-e8e5-4d29-ae97-7e14a9503439' class='xr-var-data-in' type='checkbox'><label for='data-3aa972f4-e8e5-4d29-ae97-7e14a9503439' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a791581-4cf9-4ad4-bcb0-8a4d1af300ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a791581-4cf9-4ad4-bcb0-8a4d1af300ed' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.753 5.443 4.649 ... 9.24 6.403</div><input id='attrs-5b553bbd-ebfd-4dd7-a29a-4b28a16ec788' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b553bbd-ebfd-4dd7-a29a-4b28a16ec788' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23dd80aa-6d12-49f4-81f5-162017846168' class='xr-var-data-in' type='checkbox'><label for='data-23dd80aa-6d12-49f4-81f5-162017846168' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[5.75291647],\n",
       "         [5.44320293],\n",
       "         [4.64947261],\n",
       "         ...,\n",
       "         [6.26103258],\n",
       "         [6.74222739],\n",
       "         [6.17768012]],\n",
       "\n",
       "        [[4.99497194],\n",
       "         [4.78451752],\n",
       "         [4.52971517],\n",
       "         ...,\n",
       "         [4.76813062],\n",
       "         [5.634216  ],\n",
       "         [4.71930242]],\n",
       "\n",
       "        [[5.0034959 ],\n",
       "         [4.90657537],\n",
       "         [4.92329767],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [3.78553821],\n",
       "         [2.84175721],\n",
       "         [2.51909707]],\n",
       "\n",
       "        [[2.81664768],\n",
       "         [4.09003099],\n",
       "         [4.64087193],\n",
       "         ...,\n",
       "         [4.29012915],\n",
       "         [3.82706251],\n",
       "         [3.98000262]],\n",
       "\n",
       "        [[6.09236151],\n",
       "         [7.02998798],\n",
       "         [4.93381987],\n",
       "         ...,\n",
       "         [6.7661309 ],\n",
       "         [9.2400526 ],\n",
       "         [6.403239  ]]]], shape=(1, 500, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c8a7eb43-d95a-4ad5-8e32-45d534b1d5e8' class='xr-section-summary-in' type='checkbox'  ><label for='section-c8a7eb43-d95a-4ad5-8e32-45d534b1d5e8' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e5337675-2fa2-49ad-9df8-1440cd80900d' class='xr-index-data-in' type='checkbox'/><label for='index-e5337675-2fa2-49ad-9df8-1440cd80900d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d3440b6f-64f3-4ac6-997a-85997f7b16cc' class='xr-index-data-in' type='checkbox'/><label for='index-d3440b6f-64f3-4ac6-997a-85997f7b16cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       490, 491, 492, 493, 494, 495, 496, 497, 498, 499],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3bc5a7ba-fcd1-4bd0-8459-68c575283300' class='xr-index-data-in' type='checkbox'/><label for='index-3bc5a7ba-fcd1-4bd0-8459-68c575283300' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>treated_units</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b247f625-51e3-4e2c-b3a2-c1ac5d817137' class='xr-index-data-in' type='checkbox'/><label for='index-b247f625-51e3-4e2c-b3a2-c1ac5d817137' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;UK&#x27;], dtype=&#x27;object&#x27;, name=&#x27;treated_units&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-46a8259f-c97f-4686-a59c-13c661c9781c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-46a8259f-c97f-4686-a59c-13c661c9781c' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:29.065707+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
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       "                  <input id=\"idata_observed_datad07f1800-7ba4-48e9-af91-b47f027498f9\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
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       "\n",
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       "\n",
       ".xr-var-name span,\n",
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       ".xr-index-name div,\n",
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       ".xr-attrs {\n",
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       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 488B\n",
       "Dimensions:        (obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (obs_ind, treated_units) float64 240B 4.619 4.604 ... 5.327\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:28.935117+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9387f5d2-8650-4b1d-91a2-95f49c44292e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9387f5d2-8650-4b1d-91a2-95f49c44292e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c70eff3c-6380-4b0e-b1a5-2eda16c5a568' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c70eff3c-6380-4b0e-b1a5-2eda16c5a568' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-dc3b0ab7-9879-4b32-8a67-fbd29f93a2db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc3b0ab7-9879-4b32-8a67-fbd29f93a2db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b40a3177-1b9f-4008-bf33-be23ddfc1dd6' class='xr-var-data-in' type='checkbox'><label for='data-b40a3177-1b9f-4008-bf33-be23ddfc1dd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-4a1dabf2-c5b7-4db8-9253-1b5c729e22be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a1dabf2-c5b7-4db8-9253-1b5c729e22be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6556113-a2a8-43df-97a1-447f058fdd33' class='xr-var-data-in' type='checkbox'><label for='data-a6556113-a2a8-43df-97a1-447f058fdd33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-01c9a85e-2ef3-4a78-941a-39b1bd55d147' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01c9a85e-2ef3-4a78-941a-39b1bd55d147' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.619 4.604 4.607 ... 5.297 5.327</div><input id='attrs-39789523-af01-497d-909f-81d069e54d8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-39789523-af01-497d-909f-81d069e54d8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fe1c17b-506d-47e6-aa1f-0264d8b3c36e' class='xr-var-data-in' type='checkbox'><label for='data-7fe1c17b-506d-47e6-aa1f-0264d8b3c36e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[4.61881],\n",
       "       [4.60431],\n",
       "       [4.60722],\n",
       "       [4.62152],\n",
       "       [4.6538 ],\n",
       "       [4.70655],\n",
       "       [4.73954],\n",
       "       [4.74526],\n",
       "       [4.7672 ],\n",
       "       [4.77202],\n",
       "       [4.78726],\n",
       "       [4.79335],\n",
       "       [4.82583],\n",
       "       [4.82299],\n",
       "       [4.88205],\n",
       "       [4.87   ],\n",
       "       [4.89236],\n",
       "       [4.92451],\n",
       "       [4.96229],\n",
       "       [4.98839],\n",
       "       [5.03492],\n",
       "       [5.07551],\n",
       "       [5.10988],\n",
       "       [5.13852],\n",
       "       [5.17165],\n",
       "       [5.20984],\n",
       "       [5.23783],\n",
       "       [5.27344],\n",
       "       [5.29673],\n",
       "       [5.32731]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55187a1c-436e-4de9-8754-a1b455b64606' class='xr-section-summary-in' type='checkbox'  ><label for='section-55187a1c-436e-4de9-8754-a1b455b64606' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d3a4420b-daba-44e5-a7b1-ff98a24b7547' class='xr-index-data-in' type='checkbox'/><label for='index-d3a4420b-daba-44e5-a7b1-ff98a24b7547' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>treated_units</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6904d334-1595-4662-886d-a028c309d5ee' class='xr-index-data-in' type='checkbox'/><label for='index-6904d334-1595-4662-886d-a028c309d5ee' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;UK&#x27;], dtype=&#x27;object&#x27;, name=&#x27;treated_units&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-193de259-5a44-4f0e-a28c-b34197d5f582' class='xr-section-summary-in' type='checkbox'  checked><label for='section-193de259-5a44-4f0e-a28c-b34197d5f582' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:28.935117+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
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       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 4kB\n",
       "Dimensions:  (obs_ind: 30, coeffs: 15)\n",
       "Coordinates:\n",
       "  * obs_ind  (obs_ind) int64 240B 0 1 2 3 4 5 6 7 8 ... 22 23 24 25 26 27 28 29\n",
       "  * coeffs   (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Sweden&#x27; &#x27;Switzerland&#x27;\n",
       "Data variables:\n",
       "    X        (obs_ind, coeffs) float64 4kB 3.84 0.8028 0.9412 ... 12.37 1.719\n",
       "Attributes:\n",
       "    created_at:                 2025-11-14T11:13:28.936057+00:00\n",
       "    arviz_version:              0.21.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f8ccb15d-6ef5-47c8-aa18-a6a362945eec' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f8ccb15d-6ef5-47c8-aa18-a6a362945eec' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>coeffs</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-87d60e15-86bc-41fc-a801-f7ccd6154630' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87d60e15-86bc-41fc-a801-f7ccd6154630' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-a1e466e1-fcd8-4efb-8b4b-f58e534b51f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1e466e1-fcd8-4efb-8b4b-f58e534b51f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef9341e7-e518-4ddf-9053-6bf2ecf5a787' class='xr-var-data-in' type='checkbox'><label for='data-ef9341e7-e518-4ddf-9053-6bf2ecf5a787' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-b0c9e90d-3667-44ba-92df-a1a8de3d3ede' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0c9e90d-3667-44ba-92df-a1a8de3d3ede' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2df9f5e4-e3b8-4182-a44f-cd9b14de792d' class='xr-var-data-in' type='checkbox'><label for='data-2df9f5e4-e3b8-4182-a44f-cd9b14de792d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4f4bc73e-b998-4b41-a628-82674d1a47cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4f4bc73e-b998-4b41-a628-82674d1a47cd' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>X</span></div><div class='xr-var-dims'>(obs_ind, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.84 0.8028 0.9412 ... 12.37 1.719</div><input id='attrs-e7484a87-3972-4367-9ca1-0c5f5d4459f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7484a87-3972-4367-9ca1-0c5f5d4459f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a06e3f4-357b-4d57-b798-90197b3af211' class='xr-var-data-in' type='checkbox'><label for='data-9a06e3f4-357b-4d57-b798-90197b3af211' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.84048  ,  0.802836 ,  0.94117  , 16.93824  ,  4.50096  ,\n",
       "         0.51052  ,  5.0545   ,  6.63471  ,  5.18157  ,  0.114836 ,\n",
       "         1.634391 ,  0.47336  ,  7.78753  , 10.3222   ,  1.4765317],\n",
       "       [ 3.86954  ,  0.796545 ,  0.94162  , 16.7534   ,  4.41372  ,\n",
       "         0.50829  ,  5.05375  ,  6.6453   ,  5.16171  ,  0.116259 ,\n",
       "         1.634432 ,  0.47916  ,  7.71903  , 10.32867  ,  1.485509 ],\n",
       "       [ 3.88115  ,  0.799937 ,  0.95352  , 16.82878  ,  4.42898  ,\n",
       "         0.51299  ,  5.06237  ,  6.68237  ,  5.24132  ,  0.118747 ,\n",
       "         1.640982 ,  0.48188  ,  7.724    , 10.32328  ,  1.502506 ],\n",
       "       [ 3.91028  ,  0.803823 ,  0.96117  , 17.02503  ,  4.433    ,\n",
       "         0.50903  ,  5.09832  ,  6.73155  ,  5.22482  ,  0.119302 ,\n",
       "         1.650866 ,  0.48805  ,  7.72812  , 10.37107  ,  1.5151385],\n",
       "       [ 3.92716  ,  0.80051  ,  0.96615  , 17.23041  ,  4.47128  ,\n",
       "         0.51413  ,  5.11625  ,  6.78621  ,  4.91128  ,  0.121414 ,\n",
       "         1.647748 ,  0.49349  ,  7.87891  , 10.64833  ,  1.525864 ],\n",
       "       [ 3.95387  ,  0.811277 ,  0.97567  , 17.32057  ,  4.50184  ,\n",
       "         0.52833  ,  5.14098  ,  6.93903  ,  5.10614  ,  0.122733 ,\n",
       "         1.654981 ,  0.49609  ,  7.79516  , 10.86674  ,  1.5384847],\n",
       "       [ 3.98175  ,  0.81855  ,  0.97974  , 17.44332  ,  4.57321  ,\n",
       "         0.52616  ,  5.17273  ,  6.99577  ,  5.00671  ,  0.120794 ,\n",
       "...\n",
       "         0.52588  ,  5.39537  ,  7.53046  ,  5.61836  ,  0.135719 ,\n",
       "         1.708111 ,  0.54982  ,  8.43427  , 11.82275  ,  1.6761612],\n",
       "       [ 4.50884  ,  0.856751 ,  1.03446  , 19.36275  ,  4.79998  ,\n",
       "         0.52179  ,  5.4238   ,  7.49188  ,  5.51916  ,  0.134703 ,\n",
       "         1.718281 ,  0.55348  ,  8.41262  , 11.98956  ,  1.6733119],\n",
       "       [ 4.5137   ,  0.858388 ,  1.04141  , 19.31005  ,  4.82243  ,\n",
       "         0.52973  ,  5.42994  ,  7.5471   ,  5.86313  ,  0.135616 ,\n",
       "         1.723575 ,  0.5585   ,  8.45721  , 12.10879  ,  1.6853151],\n",
       "       [ 4.56084  ,  0.863285 ,  1.0434   , 19.37835  ,  4.83698  ,\n",
       "         0.52968  ,  5.44213  ,  7.58115  ,  5.81588  ,  0.134972 ,\n",
       "         1.729509 ,  0.56733  ,  8.55631  , 12.27554  ,  1.6959884],\n",
       "       [ 4.58825  ,  0.864379 ,  1.04775  , 19.39286  ,  4.84776  ,\n",
       "         0.53265  ,  5.45297  ,  7.61443  ,  5.9103   ,  0.13584  ,\n",
       "         1.729793 ,  0.57376  ,  8.48118  , 12.36629  ,  1.7029608],\n",
       "       [ 4.62773  ,  0.873659 ,  1.04835  , 19.49923  ,  4.9036   ,\n",
       "         0.53922  ,  5.48707  ,  7.67836  ,  5.73509  ,  0.139863 ,\n",
       "         1.745688 ,  0.57866  ,  8.49252  , 12.35977  ,  1.7101124],\n",
       "       [ 4.658    ,  0.872602 ,  1.05411  , 19.40335  ,  4.96993  ,\n",
       "         0.54006  ,  5.47082  ,  7.71241  ,  6.13539  ,  0.14183  ,\n",
       "         1.749799 ,  0.58517  ,  8.48983  , 12.36546  ,  1.7190255]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-526aa48f-3c3b-4d0a-870b-794deb93a3b7' class='xr-section-summary-in' type='checkbox'  ><label for='section-526aa48f-3c3b-4d0a-870b-794deb93a3b7' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>obs_ind</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-30233171-edaf-45b0-b42a-ba2ce8776093' class='xr-index-data-in' type='checkbox'/><label for='index-30233171-edaf-45b0-b42a-ba2ce8776093' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;obs_ind&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>coeffs</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-eded30de-785f-4480-877c-c88ca6690d6b' class='xr-index-data-in' type='checkbox'/><label for='index-eded30de-785f-4480-877c-c88ca6690d6b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;coeffs&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8361551d-8b25-4817-ba99-f1848214f959' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8361551d-8b25-4817-ba99-f1848214f959' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-11-14T11:13:28.936057+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.21.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "              </ul>\n",
       "            </div>\n",
       "            <style> /* CSS stylesheet for displaying InferenceData objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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       "\n",
       "html[theme=dark],\n",
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       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
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       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
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       "\n",
       ".xr-obj-type {\n",
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       "\n",
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       "\n",
       ".xr-sections.group-sections {\n",
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       "\n",
       ".xr-section-item {\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
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       "\n",
       ".xr-section-summary {\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary > span {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
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       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
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       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
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       "\n",
       ".xr-array-wrap {\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
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       "  text-overflow: ellipsis;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       ".xr-wrap{width:700px!important;} </style>"
      ],
      "text/plain": [
       "Inference data with groups:\n",
       "\t> posterior\n",
       "\t> posterior_predictive\n",
       "\t> sample_stats\n",
       "\t> prior\n",
       "\t> prior_predictive\n",
       "\t> observed_data\n",
       "\t> constant_data"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.idata"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the MCMC chain mixing via the `Rhat` statistic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>beta[UK, Australia]</th>\n",
       "      <td>0.121</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.243</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.001</td>\n",
       "      <td>607.0</td>\n",
       "      <td>656.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Austria]</th>\n",
       "      <td>0.046</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.123</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>808.0</td>\n",
       "      <td>703.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Belgium]</th>\n",
       "      <td>0.052</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>784.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Canada]</th>\n",
       "      <td>0.038</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.077</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>472.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Denmark]</th>\n",
       "      <td>0.085</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.001</td>\n",
       "      <td>581.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Finland]</th>\n",
       "      <td>0.041</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.113</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>873.0</td>\n",
       "      <td>935.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, France]</th>\n",
       "      <td>0.031</td>\n",
       "      <td>0.028</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.084</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>749.0</td>\n",
       "      <td>728.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Germany]</th>\n",
       "      <td>0.026</td>\n",
       "      <td>0.025</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>680.0</td>\n",
       "      <td>897.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Iceland]</th>\n",
       "      <td>0.154</td>\n",
       "      <td>0.041</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>844.0</td>\n",
       "      <td>943.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Luxemburg]</th>\n",
       "      <td>0.049</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>738.0</td>\n",
       "      <td>553.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Netherlands]</th>\n",
       "      <td>0.048</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>996.0</td>\n",
       "      <td>995.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, New_Zealand]</th>\n",
       "      <td>0.062</td>\n",
       "      <td>0.055</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.164</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.001</td>\n",
       "      <td>627.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Norway]</th>\n",
       "      <td>0.082</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.156</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.001</td>\n",
       "      <td>621.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Sweden]</th>\n",
       "      <td>0.100</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>837.0</td>\n",
       "      <td>719.0</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta[UK, Switzerland]</th>\n",
       "      <td>0.065</td>\n",
       "      <td>0.057</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.172</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3963.0</td>\n",
       "      <td>2199.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y_hat_sigma[UK]</th>\n",
       "      <td>0.031</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1036.0</td>\n",
       "      <td>1488.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  \\\n",
       "beta[UK, Australia]    0.121  0.074   0.001    0.243      0.003    0.001   \n",
       "beta[UK, Austria]      0.046  0.042   0.000    0.123      0.001    0.001   \n",
       "beta[UK, Belgium]      0.052  0.048   0.000    0.140      0.001    0.001   \n",
       "beta[UK, Canada]       0.038  0.023   0.000    0.077      0.001    0.000   \n",
       "beta[UK, Denmark]      0.085  0.065   0.000    0.200      0.002    0.001   \n",
       "beta[UK, Finland]      0.041  0.039   0.000    0.113      0.001    0.001   \n",
       "beta[UK, France]       0.031  0.028   0.000    0.084      0.001    0.001   \n",
       "beta[UK, Germany]      0.026  0.025   0.000    0.072      0.001    0.001   \n",
       "beta[UK, Iceland]      0.154  0.041   0.075    0.230      0.001    0.001   \n",
       "beta[UK, Luxemburg]    0.049  0.045   0.000    0.134      0.001    0.001   \n",
       "beta[UK, Netherlands]  0.048  0.043   0.000    0.126      0.001    0.001   \n",
       "beta[UK, New_Zealand]  0.062  0.055   0.000    0.164      0.002    0.001   \n",
       "beta[UK, Norway]       0.082  0.045   0.000    0.156      0.002    0.001   \n",
       "beta[UK, Sweden]       0.100  0.031   0.043    0.160      0.001    0.001   \n",
       "beta[UK, Switzerland]  0.065  0.057   0.000    0.172      0.001    0.001   \n",
       "y_hat_sigma[UK]        0.031  0.005   0.023    0.040      0.000    0.000   \n",
       "\n",
       "                       ess_bulk  ess_tail  r_hat  \n",
       "beta[UK, Australia]       607.0     656.0   1.00  \n",
       "beta[UK, Austria]         808.0     703.0   1.01  \n",
       "beta[UK, Belgium]         784.0     618.0   1.00  \n",
       "beta[UK, Canada]          472.0     476.0   1.01  \n",
       "beta[UK, Denmark]         581.0     573.0   1.00  \n",
       "beta[UK, Finland]         873.0     935.0   1.00  \n",
       "beta[UK, France]          749.0     728.0   1.00  \n",
       "beta[UK, Germany]         680.0     897.0   1.00  \n",
       "beta[UK, Iceland]         844.0     943.0   1.00  \n",
       "beta[UK, Luxemburg]       738.0     553.0   1.00  \n",
       "beta[UK, Netherlands]     996.0     995.0   1.00  \n",
       "beta[UK, New_Zealand]     627.0     605.0   1.00  \n",
       "beta[UK, Norway]          621.0     568.0   1.01  \n",
       "beta[UK, Sweden]          837.0     719.0   1.01  \n",
       "beta[UK, Switzerland]    3963.0    2199.0   1.00  \n",
       "y_hat_sigma[UK]          1036.0    1488.0   1.00  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(result.idata, var_names=[\"~mu\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can inspect the traces in more detail with:\n",
    "\n",
    "```python\n",
    "az.plot_trace(result.idata, var_names=\"~mu\", compact=False);\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x800 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 811,
       "width": 711
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.style.use(\"arviz-darkgrid\")\n",
    "\n",
    "fig, ax = result.plot(plot_predictors=False)\n",
    "\n",
    "for i in [0, 1, 2]:\n",
    "    ax[i].set(ylabel=\"Trillion USD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================SyntheticControl================================\n",
      "Control units: ['Australia', 'Austria', 'Belgium', 'Canada', 'Denmark', 'Finland', 'France', 'Germany', 'Iceland', 'Luxemburg', 'Netherlands', 'New_Zealand', 'Norway', 'Sweden', 'Switzerland']\n",
      "Treated unit: UK\n",
      "Model coefficients:\n",
      "    Australia    0.12, 94% HDI [0.0086, 0.27]\n",
      "    Austria      0.046, 94% HDI [0.0013, 0.15]\n",
      "    Belgium      0.052, 94% HDI [0.0016, 0.17]\n",
      "    Canada       0.038, 94% HDI [0.0025, 0.085]\n",
      "    Denmark      0.085, 94% HDI [0.0031, 0.23]\n",
      "    Finland      0.041, 94% HDI [0.0015, 0.14]\n",
      "    France       0.031, 94% HDI [0.0011, 0.1]\n",
      "    Germany      0.026, 94% HDI [0.00096, 0.086]\n",
      "    Iceland      0.15, 94% HDI [0.075, 0.23]\n",
      "    Luxemburg    0.049, 94% HDI [0.0011, 0.16]\n",
      "    Netherlands  0.048, 94% HDI [0.0021, 0.16]\n",
      "    New_Zealand  0.062, 94% HDI [0.0015, 0.19]\n",
      "    Norway       0.082, 94% HDI [0.0076, 0.17]\n",
      "    Sweden       0.1, 94% HDI [0.039, 0.16]\n",
      "    Switzerland  0.065, 94% HDI [0.0024, 0.2]\n",
      "    y_hat_sigma  0.031, 94% HDI [0.023, 0.041]\n"
     ]
    }
   ],
   "source": [
    "result.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effect Summary Reporting\n",
    "\n",
    "For decision-making, you often need a concise summary of the causal effect with key statistics. The `effect_summary()` method provides a decision-ready report with average and cumulative effects, HDI intervals, tail probabilities, and relative effects. This provides a comprehensive summary without manual post-processing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>hdi_lower</th>\n",
       "      <th>hdi_upper</th>\n",
       "      <th>p_gt_0</th>\n",
       "      <th>relative_mean</th>\n",
       "      <th>relative_hdi_lower</th>\n",
       "      <th>relative_hdi_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>average</th>\n",
       "      <td>-0.178323</td>\n",
       "      <td>-0.179121</td>\n",
       "      <td>-0.227586</td>\n",
       "      <td>-0.127143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.164222</td>\n",
       "      <td>-4.005843</td>\n",
       "      <td>-2.278178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumulative</th>\n",
       "      <td>-4.101438</td>\n",
       "      <td>-4.119792</td>\n",
       "      <td>-5.234484</td>\n",
       "      <td>-2.924293</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.164222</td>\n",
       "      <td>-4.005843</td>\n",
       "      <td>-2.278178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mean    median  hdi_lower  hdi_upper  p_gt_0  relative_mean  \\\n",
       "average    -0.178323 -0.179121  -0.227586  -0.127143     0.0      -3.164222   \n",
       "cumulative -4.101438 -4.119792  -5.234484  -2.924293     0.0      -3.164222   \n",
       "\n",
       "            relative_hdi_lower  relative_hdi_upper  \n",
       "average              -4.005843           -2.278178  \n",
       "cumulative           -4.005843           -2.278178  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate effect summary for the full post-period\n",
    "stats = result.effect_summary()\n",
    "stats.table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Post-period (2016-07-01 00:00:00 to 2022-01-01 00:00:00), the average effect was -0.18 (95% HDI [-0.23, -0.13]), with a posterior probability of an increase of 0.000. The cumulative effect was -4.10 (95% HDI [-5.23, -2.92]); probability of an increase 0.000. Relative to the counterfactual, this equals -3.16% on average (95% HDI [-4.01%, -2.28%]).\n"
     ]
    }
   ],
   "source": [
    "# View the prose summary\n",
    "print(stats.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>hdi_lower</th>\n",
       "      <th>hdi_upper</th>\n",
       "      <th>p_gt_0</th>\n",
       "      <th>relative_mean</th>\n",
       "      <th>relative_hdi_lower</th>\n",
       "      <th>relative_hdi_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>average</th>\n",
       "      <td>-0.021407</td>\n",
       "      <td>-0.021822</td>\n",
       "      <td>-0.064357</td>\n",
       "      <td>0.021860</td>\n",
       "      <td>0.1635</td>\n",
       "      <td>-0.393064</td>\n",
       "      <td>-1.17724</td>\n",
       "      <td>0.406281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumulative</th>\n",
       "      <td>-0.085627</td>\n",
       "      <td>-0.087289</td>\n",
       "      <td>-0.257429</td>\n",
       "      <td>0.087441</td>\n",
       "      <td>0.1635</td>\n",
       "      <td>-0.393064</td>\n",
       "      <td>-1.17724</td>\n",
       "      <td>0.406281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mean    median  hdi_lower  hdi_upper  p_gt_0  relative_mean  \\\n",
       "average    -0.021407 -0.021822  -0.064357   0.021860  0.1635      -0.393064   \n",
       "cumulative -0.085627 -0.087289  -0.257429   0.087441  0.1635      -0.393064   \n",
       "\n",
       "            relative_hdi_lower  relative_hdi_upper  \n",
       "average               -1.17724            0.406281  \n",
       "cumulative            -1.17724            0.406281  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# You can also analyze a specific time window, e.g., the first year after Brexit\n",
    "stats_window = result.effect_summary(\n",
    "    window=(pd.to_datetime(\"2016-06-24\"), pd.to_datetime(\"2017-06-24\"))\n",
    ")\n",
    "stats_window.table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom priors\n",
    "\n",
    "The analysis above is all based upon the default priors for the `WeightedSumFitter` class. But this might not always be appropriate. In particular the default Priors are [Dirichlet distributed](https://en.wikipedia.org/wiki/Dirichlet_distribution) with an alpha parameter of 1. This corresponds to a uniform prior over the simplex.\n",
    "\n",
    "But we might have different prior beliefs. For example, we might think that some control units will play a larger role and some control units will be irrelevant. In which case, we could use as less concentrated prior, such as $\\mathrm{Dirichlet}(0.1)$.\n",
    "\n",
    "We can do this in the code below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [beta, y_hat_sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "232bff5a8647475db754021a68f41aef",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 81 seconds.\n",
      "There were 168 divergences after tuning. Increase `target_accept` or reparameterize.\n",
      "Chain 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n",
      "Sampling: [beta, y_hat, y_hat_sigma]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n"
     ]
    }
   ],
   "source": [
    "n_control_units = len(other_countries)\n",
    "\n",
    "result_custom = cp.SyntheticControl(\n",
    "    df,\n",
    "    treatment_time,\n",
    "    control_units=other_countries,\n",
    "    treated_units=[target_country],\n",
    "    model=cp.pymc_models.WeightedSumFitter(\n",
    "        sample_kwargs=sample_kwargs,\n",
    "        priors={\n",
    "            \"beta\": Prior(\n",
    "                \"Dirichlet\",\n",
    "                a=0.1 * np.ones(n_control_units),\n",
    "                dims=[\"treated_units\", \"coeffs\"],\n",
    "            ),\n",
    "        },\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main results plot shows only minor differences in terms of fitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x800 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 811,
       "width": 711
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = result_custom.plot(plot_predictors=False)\n",
    "\n",
    "for i in [0, 1, 2]:\n",
    "    ax[i].set(ylabel=\"Trillion USD\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also examine the effect of changing the Dirichlet prior on the posterior distribution of weights. TWe can see that the custom prior of $\\mathrm{Dirichlet}(0.1)$ results in more sparse weights over control countries. The posterior of many countries are more concentrated near zero (e.g. Austria, Canada, Germany, etc), while others have increased in importance (e.g. Denmark, and Australia).\n",
    "\n",
    "This is a rich area for discussion, but the key point is that users can define their own prior beliefs about the weights in the synthetic control model. There are some benefits from having 'sparsifying' priors in that they can help identify a smaller set of key control units that are most relevant to constructing the synthetic control."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1011,
       "width": 811
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_forest(\n",
    "    [result.idata, result_custom.idata],\n",
    "    model_names=[\"Default prior\", \"Custom prior\"],\n",
    "    var_names=[\"beta\", \"y_hat_sigma\"],\n",
    "    combined=True,\n",
    "    figsize=(8, 10),\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    ":::{bibliography}\n",
    ":filter: docname in docnames\n",
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