{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "domestic-remove",
   "metadata": {},
   "source": [
    "(bart_heteroscedasticity)=\n",
    "# Modeling Heteroscedasticity with BART\n",
    "\n",
    ":::{post} January, 2023\n",
    ":tags: BART, regression\n",
    ":category: beginner, reference\n",
    ":author: Juan Orduz\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72588976-efc3-4adc-bec2-bc5b6ac4b7e1",
   "metadata": {},
   "source": [
    "In this notebook we show how to use BART to model heteroscedasticity as described in Section 4.1 of [`pymc-bart`](https://github.com/pymc-devs/pymc-bart)'s paper {cite:p}`quiroga2022bart`. We use the `marketing` data set provided by the R package `datarium` {cite:p}`kassambara2019datarium`. The idea is to model a marketing channel contribution to sales as a function of budget."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "elect-softball",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymc as pm\n",
    "import pymc_bart as pmb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "level-balance",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = \"retina\"\n",
    "az.style.use(\"arviz-variat\")\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 6]\n",
    "rng = np.random.default_rng(42)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cae4407",
   "metadata": {},
   "source": [
    "## Read Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21e66b38",
   "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>youtube</th>\n",
       "      <th>facebook</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>276.12</td>\n",
       "      <td>45.36</td>\n",
       "      <td>83.04</td>\n",
       "      <td>26.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53.40</td>\n",
       "      <td>47.16</td>\n",
       "      <td>54.12</td>\n",
       "      <td>12.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20.64</td>\n",
       "      <td>55.08</td>\n",
       "      <td>83.16</td>\n",
       "      <td>11.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>181.80</td>\n",
       "      <td>49.56</td>\n",
       "      <td>70.20</td>\n",
       "      <td>22.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>216.96</td>\n",
       "      <td>12.96</td>\n",
       "      <td>70.08</td>\n",
       "      <td>15.48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   youtube  facebook  newspaper  sales\n",
       "0   276.12     45.36      83.04  26.52\n",
       "1    53.40     47.16      54.12  12.48\n",
       "2    20.64     55.08      83.16  11.16\n",
       "3   181.80     49.56      70.20  22.20\n",
       "4   216.96     12.96      70.08  15.48"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "try:\n",
    "    df = pd.read_csv(os.path.join(\"..\", \"data\", \"marketing.csv\"), sep=\";\", decimal=\",\")\n",
    "except FileNotFoundError:\n",
    "    df = pd.read_csv(pm.get_data(\"marketing.csv\"), sep=\";\", decimal=\",\")\n",
    "\n",
    "n_obs = df.shape[0]\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d6364a9",
   "metadata": {},
   "source": [
    "## EDA\n",
    "\n",
    "We start by looking into the data. We are going to focus on *Youtube*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8bbae786",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1223,
       "width": 2023
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(df[\"youtube\"], df[\"sales\"], \"o\", c=\"C0\")\n",
    "ax.set(title=\"Sales as a function of Youtube budget\", xlabel=\"budget\", ylabel=\"sales\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c3971f2",
   "metadata": {},
   "source": [
    "We clearly see that both the mean and variance are increasing as a function of budget. One possibility is to manually select an explicit parametrization of these functions, e.g. square root or logarithm. However, in this example we want to learn these functions from the data using a BART model."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8a3ce48",
   "metadata": {},
   "source": [
    "## Model Specification\n",
    "\n",
    "We proceed to prepare the data for modeling. We are going to use the `budget` as the predictor and `sales` as the response."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "db0bbf73",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df[\"youtube\"].to_numpy().reshape(-1, 1)\n",
    "Y = df[\"sales\"].to_numpy()"
   ]
  },
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   "id": "a29b706c",
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   "source": [
    "Next, we specify the model. Note that we just need one BART distribution which can be vectorized to model both the mean and variance. We use a Gamma distribution as likelihood as we expect the sales to be positive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6d85d918",
   "metadata": {},
   "outputs": [
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   "source": [
    "with pm.Model() as model_marketing_full:\n",
    "    w = pmb.BART(\"w\", X=X, Y=np.log(Y), m=100, shape=(2, n_obs))\n",
    "    y = pm.Gamma(\"y\", mu=pm.math.exp(w[0]), sigma=pm.math.exp(w[1]), observed=Y)\n",
    "\n",
    "pm.model_to_graphviz(model=model_marketing_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9aa885a3",
   "metadata": {},
   "source": [
    "We now fit the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "796874ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "PGBART: [w]\n"
     ]
    },
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       "version_minor": 0
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       "Output()"
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    },
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     "metadata": {},
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 150 seconds.\n",
      "Sampling: [y]\n"
     ]
    },
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       "Output()"
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      "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"
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   "source": [
    "with model_marketing_full:\n",
    "    idata_marketing_full = pm.sample(2000, random_seed=rng, compute_convergence_checks=False)\n",
    "    posterior_predictive_marketing_full = pm.sample_posterior_predictive(\n",
    "        trace=idata_marketing_full, random_seed=rng\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eba7cee5",
   "metadata": {},
   "source": [
    "## Results\n",
    "\n",
    "We can now visualize the posterior predictive distribution of the mean and the likelihood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "04ca4edc",
   "metadata": {},
   "outputs": [
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       "}\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",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\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",
       "  border-color: var(--xr-background-color-row-even);\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",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\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-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\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",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataTree&gt;\n",
       "Group: /\n",
       "├── Group: /posterior_predictive\n",
       "│       Dimensions:  (chain: 4, draw: 2000, y_dim_0: 200)\n",
       "│       Coordinates:\n",
       "│         * chain    (chain) int64 32B 0 1 2 3\n",
       "│         * draw     (draw) int64 16kB 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n",
       "│         * y_dim_0  (y_dim_0) int64 2kB 0 1 2 3 4 5 6 7 ... 193 194 195 196 197 198 199\n",
       "│       Data variables:\n",
       "│           y        (chain, draw, y_dim_0) float64 13MB 28.37 10.13 ... 25.83 13.69\n",
       "│       Attributes:\n",
       "│           created_at:                 2026-04-25T08:24:51.846027+00:00\n",
       "│           creation_library:           ArviZ\n",
       "│           creation_library_version:   1.1.1dev0\n",
       "│           creation_library_language:  Python\n",
       "│           inference_library:          pymc\n",
       "│           inference_library_version:  5.28.0+58.gf58491a3\n",
       "│           sample_dims:                [&#x27;chain&#x27;, &#x27;draw&#x27;]\n",
       "└── Group: /observed_data\n",
       "        Dimensions:  (y_dim_0: 200)\n",
       "        Coordinates:\n",
       "          * y_dim_0  (y_dim_0) int64 2kB 0 1 2 3 4 5 6 7 ... 193 194 195 196 197 198 199\n",
       "        Data variables:\n",
       "            y        (y_dim_0) float64 2kB 26.52 12.48 11.16 22.2 ... 15.36 30.6 16.08\n",
       "        Attributes:\n",
       "            created_at:                 2026-04-25T08:24:51.847700+00:00\n",
       "            creation_library:           ArviZ\n",
       "            creation_library_version:   1.1.1dev0\n",
       "            creation_library_language:  Python\n",
       "            inference_library:          pymc\n",
       "            inference_library_version:  5.28.0+58.gf58491a3\n",
       "            sample_dims:                []</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-children'><div class='xr-group-box'><div class='xr-group-box-vline' style='height: 100%'></div><div class='xr-group-box-hline'></div><div class='xr-group-box-contents'><input id='group-1884ecfd-4d57-4687-b580-ba0e814f9f74' type='checkbox' checked /><label for='group-1884ecfd-4d57-4687-b580-ba0e814f9f74' title='Expand/collapse group'>/posterior_predictive<span>(11)</span></label><ul class='xr-sections'><li class='xr-section-item'><input id='section-d9001c50-05c5-4f8a-b9fa-cae00b92226e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d9001c50-05c5-4f8a-b9fa-cae00b92226e' class='xr-section-summary'>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>: 2000</li><li><span class='xr-has-index'>y_dim_0</span>: 200</li></ul></div></li><li class='xr-section-item'><input id='section-8eb40fe6-e294-4215-9c2a-c36dfacacb14' class='xr-section-summary-in' type='checkbox' checked /><label for='section-8eb40fe6-e294-4215-9c2a-c36dfacacb14' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <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 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-d9eeb291-0956-431e-b6e2-b501adff5e16' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d9eeb291-0956-431e-b6e2-b501adff5e16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cdd2c8e-ccee-4639-a86d-6460c66b7189' class='xr-var-data-in' type='checkbox'><label for='data-7cdd2c8e-ccee-4639-a86d-6460c66b7189' 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 ... 1996 1997 1998 1999</div><input id='attrs-99f25b73-9da1-4692-8aab-38bd9e7645dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99f25b73-9da1-4692-8aab-38bd9e7645dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c43f46fb-0614-4017-bdf0-30fa984719b7' class='xr-var-data-in' type='checkbox'><label for='data-c43f46fb-0614-4017-bdf0-30fa984719b7' 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, ..., 1997, 1998, 1999], shape=(2000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_dim_0</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-5180f786-c3a0-42e5-bbcd-3ad6706a1b0b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5180f786-c3a0-42e5-bbcd-3ad6706a1b0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-665af24e-a8c2-4d14-8540-2edf850495e5' class='xr-var-data-in' type='checkbox'><label for='data-665af24e-a8c2-4d14-8540-2edf850495e5' 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,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139,140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153,154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7bcdc107-a0a1-4097-88b1-a9c76070d119' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7bcdc107-a0a1-4097-88b1-a9c76070d119' class='xr-section-summary' title='Expand/collapse section'>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</span></div><div class='xr-var-dims'>(chain, draw, y_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>28.37 10.13 9.285 ... 25.83 13.69</div><input id='attrs-581f5043-b441-4308-9019-ba55e5169493' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-581f5043-b441-4308-9019-ba55e5169493' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4236b44c-4b4d-47aa-ba77-727208e7e4e9' class='xr-var-data-in' type='checkbox'><label for='data-4236b44c-4b4d-47aa-ba77-727208e7e4e9' 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([[[28.36515905, 10.13243719,  9.28531462, ..., 17.8635317 ,13.60805225, 23.71337278],[16.01712043, 11.44802714,  7.71826756, ..., 18.54174372,17.98656282, 17.11186009],[27.22952529, 11.11619966,  6.9456162 , ..., 18.80241215,32.47463896, 13.94624846],...,[26.85990694, 13.72720789,  7.71052641, ..., 24.85951242,40.93342612, 15.61255083],[25.45195329, 11.83842857, 11.24327818, ..., 22.34880627,19.72729055, 24.15831407],[17.49892068, 12.49573609, 10.51674975, ..., 19.97979101,25.04572659, 19.25197057]],[[31.26226839, 13.21542359,  8.60974728, ..., 20.7897619 ,18.18502283, 16.80637584],[14.34889506,  8.39085474,  8.91716332, ..., 20.27154713,29.43639028, 23.64317153],[19.94739967, 12.78002473, 11.02530363, ..., 16.27998953,31.4805461 , 24.73454273],...[12.2951575 , 16.39532843,  8.02298514, ..., 18.61947698,23.08728123, 18.3355571 ],[17.93951011, 10.43174129,  8.96727105, ..., 19.78067883,22.10874961, 33.4276009 ],[16.4915944 ,  8.9833873 ,  7.93501012, ..., 18.35377923,20.06312781, 28.84780099]],[[17.97314116, 13.91682016,  7.21187568, ..., 17.19677247,22.42245555, 17.77454129],[17.14713155,  9.42115884,  9.78229146, ..., 19.59049059,18.85905945, 17.05628507],[20.48191522, 13.5320423 , 12.08411001, ..., 14.76742302,22.69731055, 24.62406661],...,[31.45073611,  9.35298342,  6.59502575, ..., 22.42870368,25.25801507, 24.19267011],[19.49592529, 14.37335088,  7.46871015, ..., 15.12362813,23.36711273, 24.55110372],[20.99578658, 13.08554341,  8.58349137, ..., 20.53121747,25.83249909, 13.69475558]]], shape=(4, 2000, 200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4e687eb3-9b64-4d5a-8aac-42735e50c687' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4e687eb3-9b64-4d5a-8aac-42735e50c687' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(7)</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>2026-04-25T08:24:51.846027+00:00</dd><dt><span>creation_library :</span></dt><dd>ArviZ</dd><dt><span>creation_library_version :</span></dt><dd>1.1.1dev0</dd><dt><span>creation_library_language :</span></dt><dd>Python</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.28.0+58.gf58491a3</dd><dt><span>sample_dims :</span></dt><dd>[&#x27;chain&#x27;, &#x27;draw&#x27;]</dd></dl></div></li></ul></div></div><div class='xr-group-box'><div class='xr-group-box-vline' style='height: 1.2em'></div><div class='xr-group-box-hline'></div><div class='xr-group-box-contents'><input id='group-000df0d9-0bcd-4847-875c-b2d0ad64682a' type='checkbox' checked /><label for='group-000df0d9-0bcd-4847-875c-b2d0ad64682a' title='Expand/collapse group'>/observed_data<span>(9)</span></label><ul class='xr-sections'><li class='xr-section-item'><input id='section-b1c88805-9687-4b4d-b867-ce3fd789490e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-b1c88805-9687-4b4d-b867-ce3fd789490e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y_dim_0</span>: 200</li></ul></div></li><li class='xr-section-item'><input id='section-549acf82-10c4-4d5a-a5e3-016b627b7ade' class='xr-section-summary-in' type='checkbox' checked /><label for='section-549acf82-10c4-4d5a-a5e3-016b627b7ade' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <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 class='xr-has-index'>y_dim_0</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-27b43c73-55a0-437f-b654-dcf4a4df6ba9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27b43c73-55a0-437f-b654-dcf4a4df6ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5539f962-ab59-47e8-82f6-d75a2bc645af' class='xr-var-data-in' type='checkbox'><label for='data-5539f962-ab59-47e8-82f6-d75a2bc645af' 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,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139,140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153,154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18006e90-a945-49e4-8ad0-2fb397861613' class='xr-section-summary-in' type='checkbox' checked /><label for='section-18006e90-a945-49e4-8ad0-2fb397861613' class='xr-section-summary' title='Expand/collapse section'>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</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>26.52 12.48 11.16 ... 30.6 16.08</div><input id='attrs-4b455888-1d6e-4353-a53b-0df02e188af7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b455888-1d6e-4353-a53b-0df02e188af7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86b097e0-6b25-4e50-8a55-8c4c50d3d5d0' class='xr-var-data-in' type='checkbox'><label for='data-86b097e0-6b25-4e50-8a55-8c4c50d3d5d0' 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([26.52, 12.48, 11.16, 22.2 , 15.48,  8.64, 14.16, 15.84,  5.76,12.72, 10.32, 20.88, 11.04, 11.64, 22.8 , 26.88, 15.  , 29.28,13.56, 17.52, 21.6 , 15.  ,  6.72, 18.6 , 11.64, 14.4 , 18.  ,19.08, 22.68, 12.6 , 25.68, 14.28, 11.52, 20.88, 11.4 , 15.36,30.48, 17.64, 12.12, 25.8 , 19.92, 20.52, 24.84, 15.48, 10.2 ,17.88, 12.72, 27.84, 17.76, 11.64, 13.68, 12.84, 27.12, 25.44,24.24, 28.44,  6.6 , 15.84, 28.56, 22.08,  9.72, 29.04, 18.84,16.8 , 21.6 , 11.16, 11.4 , 16.08, 22.68, 26.76, 21.96, 14.88,10.56, 13.2 , 20.4 , 10.44,  8.28, 17.04,  6.36, 13.2 , 14.16,14.76, 13.56, 16.32, 26.04, 18.24, 14.4 , 19.2 , 15.48, 20.04,13.44,  8.76, 23.28, 26.64, 13.8 , 20.28, 14.04, 18.6 , 30.48,20.64, 14.04, 28.56, 17.76, 17.64, 24.84, 23.04,  8.64, 10.44,6.36, 23.76, 16.08, 26.16, 16.92, 19.08, 17.52, 15.12, 14.64,11.28, 19.08,  7.92, 18.6 ,  8.4 , 13.92, 18.24, 23.64, 12.72,7.92, 10.56, 29.64, 11.64,  1.92, 15.24,  6.84, 23.52, 12.96,13.92, 11.4 , 24.96, 11.52, 24.84, 13.08, 23.04, 24.12, 12.48,13.68, 12.36, 15.84, 30.48, 13.08, 12.12, 19.32, 13.92, 19.92,22.8 , 18.72,  3.84, 18.36, 12.12,  8.76, 15.48, 17.28, 15.96,17.88, 21.6 , 14.28, 14.28,  9.6 , 14.64, 20.52, 18.  , 10.08,17.4 ,  9.12, 14.04, 13.8 , 32.4 , 24.24, 14.04, 14.16, 15.12,12.6 , 14.64, 10.44, 31.44, 21.12, 27.12, 12.36, 20.76, 19.08,8.04, 12.96, 11.88,  7.08, 23.52, 20.76,  9.12, 11.64, 15.36,30.6 , 16.08])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-70c6d833-c9b5-45ec-aa94-ffbb60195551' class='xr-section-summary-in' type='checkbox' checked /><label for='section-70c6d833-c9b5-45ec-aa94-ffbb60195551' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(7)</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>2026-04-25T08:24:51.847700+00:00</dd><dt><span>creation_library :</span></dt><dd>ArviZ</dd><dt><span>creation_library_version :</span></dt><dd>1.1.1dev0</dd><dt><span>creation_library_language :</span></dt><dd>Python</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.28.0+58.gf58491a3</dd><dt><span>sample_dims :</span></dt><dd>[]</dd></dl></div></li></ul></div></div></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataTree>\n",
       "Group: /\n",
       "├── Group: /posterior_predictive\n",
       "│       Dimensions:  (chain: 4, draw: 2000, y_dim_0: 200)\n",
       "│       Coordinates:\n",
       "│         * chain    (chain) int64 32B 0 1 2 3\n",
       "│         * draw     (draw) int64 16kB 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n",
       "│         * y_dim_0  (y_dim_0) int64 2kB 0 1 2 3 4 5 6 7 ... 193 194 195 196 197 198 199\n",
       "│       Data variables:\n",
       "│           y        (chain, draw, y_dim_0) float64 13MB 28.37 10.13 ... 25.83 13.69\n",
       "│       Attributes:\n",
       "│           created_at:                 2026-04-25T08:24:51.846027+00:00\n",
       "│           creation_library:           ArviZ\n",
       "│           creation_library_version:   1.1.1dev0\n",
       "│           creation_library_language:  Python\n",
       "│           inference_library:          pymc\n",
       "│           inference_library_version:  5.28.0+58.gf58491a3\n",
       "│           sample_dims:                ['chain', 'draw']\n",
       "└── Group: /observed_data\n",
       "        Dimensions:  (y_dim_0: 200)\n",
       "        Coordinates:\n",
       "          * y_dim_0  (y_dim_0) int64 2kB 0 1 2 3 4 5 6 7 ... 193 194 195 196 197 198 199\n",
       "        Data variables:\n",
       "            y        (y_dim_0) float64 2kB 26.52 12.48 11.16 22.2 ... 15.36 30.6 16.08\n",
       "        Attributes:\n",
       "            created_at:                 2026-04-25T08:24:51.847700+00:00\n",
       "            creation_library:           ArviZ\n",
       "            creation_library_version:   1.1.1dev0\n",
       "            creation_library_language:  Python\n",
       "            inference_library:          pymc\n",
       "            inference_library_version:  5.28.0+58.gf58491a3\n",
       "            sample_dims:                []"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posterior_predictive_marketing_full"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c2ffec14",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x643.064 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 666,
       "width": 2023
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt_plot = az.from_dict(\n",
    "    {\n",
    "        \"posterior_predictive\": {\n",
    "            \"y\": posterior_predictive_marketing_full.posterior_predictive[\"y\"]\n",
    "        },\n",
    "        \"observed_data\": {\"y\": df[\"sales\"].values},\n",
    "        \"constant_data\": {\"budget\": X[:, 0]},\n",
    "    },\n",
    "    dims={\n",
    "        \"y\": [\"budget_dim\"],\n",
    "        \"budget\": [\"budget_dim\"],\n",
    "    },\n",
    ")\n",
    "\n",
    "az.plot_lm(dt_plot, x=\"budget\", y=\"y\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1775acb",
   "metadata": {},
   "source": [
    "The fit looks good! In fact, we see that the mean and variance increase as a function of the budget."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b743d58b-2678-4e17-9947-a8fe4ed03e21",
   "metadata": {},
   "source": [
    "## Authors\n",
    "- Authored by [Juan Orduz](https://juanitorduz.github.io/) in Feb, 2023 \n",
    "- Rerun by Osvaldo Martin in Mar, 2023\n",
    "- Rerun by Osvaldo Martin in Nov, 2023\n",
    "- Rerun by Osvaldo Martin in Dec, 2025\n",
    "- Rerun by Osvaldo Martin in Apr, 2026"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "closed-frank",
   "metadata": {},
   "source": [
    "## References\n",
    ":::{bibliography}\n",
    ":filter: docname in docnames\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0717070c-04aa-4836-ab95-6b3eff0dcaaf",
   "metadata": {},
   "source": [
    "## Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "sound-calculation",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Sat, 25 Apr 2026\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.14.4\n",
      "IPython version      : 9.12.0\n",
      "\n",
      "pytensor: 2.38.0+133.g80cc113b5\n",
      "\n",
      "arviz     : 1.1.0\n",
      "matplotlib: 3.10.8\n",
      "numpy     : 2.4.4\n",
      "pandas    : 3.0.2\n",
      "pymc      : 5.28.0+58.gf58491a3\n",
      "pymc_bart : 0.11.0\n",
      "\n",
      "Watermark: 2.6.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w -p pytensor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e4386fc-4de9-4535-a160-d929315633ef",
   "metadata": {},
   "source": [
    ":::{include} ../page_footer.md\n",
    ":::"
   ]
  }
 ],
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