{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(censored_data)=\n",
    "# Censored Data Models\n",
    "\n",
    ":::{post} May, 2022\n",
    ":tags: censored, survival analysis \n",
    ":category: intermediate, how-to\n",
    ":author: Luis Mario Domenzain\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from copy import copy\n",
    "\n",
    "import arviz.preview as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pymc as pm\n",
    "\n",
    "from numpy.random import default_rng"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "rng = default_rng(1234)\n",
    "az.style.use(\"arviz-variat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[This example notebook on Bayesian survival\n",
    "analysis](https://www.pymc.io/projects/examples/en/latest/survival_analysis/survival_analysis.html) touches on the\n",
    "point of censored data. _Censoring_ is a form of missing-data problem, in which\n",
    "observations greater than a certain threshold are clipped down to that\n",
    "threshold, or observations less than a certain threshold are clipped up to that\n",
    "threshold, or both. These are called right, left and interval censoring,\n",
    "respectively. In this example notebook we consider interval censoring.\n",
    "\n",
    "Censored data arises in many modelling problems. Two common examples are:\n",
    "\n",
    "1. _Survival analysis:_ when studying the effect of a certain medical treatment\n",
    "   on survival times, it is impossible to prolong the study until all subjects\n",
    "   have died. At the end of the study, the only data collected for many patients\n",
    "   is that they were still alive for a time period $T$ after the treatment was\n",
    "   administered: in reality, their true survival times are greater than $T$.\n",
    "\n",
    "2. _Sensor saturation:_ a sensor might have a limited range and the upper and\n",
    "   lower limits would simply be the highest and lowest values a sensor can\n",
    "   report. For instance, many mercury thermometers only report a very narrow\n",
    "   range of temperatures.\n",
    "\n",
    "This example notebook presents two different ways of dealing with censored data\n",
    "in PyMC:\n",
    "\n",
    "1. An imputed censored model, which represents censored data as parameters and\n",
    "   makes up plausible values for all censored values. As a result of this\n",
    "   imputation, this model is capable of generating plausible sets of made-up\n",
    "   values that would have been censored. Each censored element introduces a\n",
    "   random variable.\n",
    "\n",
    "2. An unimputed censored model, where the censored data are integrated out and\n",
    "   accounted for only through the log-likelihood. This method deals more\n",
    "   adequately with large amounts of censored data and converges more quickly.\n",
    "\n",
    "To establish a baseline we compare to an uncensored model of the uncensored\n",
    "data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Produce normally distributed samples\n",
    "size = 500\n",
    "true_mu = 13.0\n",
    "true_sigma = 5.0\n",
    "samples = rng.normal(true_mu, true_sigma, size)\n",
    "\n",
    "# Set censoring limits\n",
    "low = 3.0\n",
    "high = 16.0\n",
    "\n",
    "\n",
    "def censor(x, low, high):\n",
    "    x = copy(x)\n",
    "    x[x <= low] = low\n",
    "    x[x >= high] = high\n",
    "    return x\n",
    "\n",
    "\n",
    "# Censor samples\n",
    "censored = censor(samples, low, high)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 623,
       "width": 2023
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize uncensored and censored data\n",
    "_, ax = plt.subplots(figsize=(10, 3))\n",
    "edges = np.linspace(-5, 35, 30)\n",
    "ax.hist(samples, bins=edges, density=True, histtype=\"stepfilled\", alpha=0.4, label=\"Uncensored\")\n",
    "ax.hist(censored, bins=edges, density=True, histtype=\"stepfilled\", alpha=0.4, label=\"Censored\")\n",
    "[ax.axvline(x=x, c=\"k\", ls=\"--\") for x in [low, high]]\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Uncensored Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def uncensored_model(data):\n",
    "    with pm.Model() as model:\n",
    "        mu = pm.Normal(\"mu\", mu=((high - low) / 2) + low, sigma=(high - low))\n",
    "        sigma = pm.HalfNormal(\"sigma\", sigma=(high - low) / 2.0)\n",
    "        observed = pm.Normal(\"observed\", mu=mu, sigma=sigma, observed=data)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We should predict that running the uncensored model on uncensored data, we will get reasonable estimates of the mean and variance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [mu, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b228a609be604a6791c913a7d92229d7",
       "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 1 seconds.\n"
     ]
    }
   ],
   "source": [
    "uncensored_model_1 = uncensored_model(samples)\n",
    "with uncensored_model_1:\n",
    "    idata = pm.sample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x535.887 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = az.plot_dist(idata)\n",
    "az.add_lines(pc, {\"mu\": true_mu, \"sigma\": true_sigma});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And that is exactly what we find. \n",
    "\n",
    "The problem however, is that in censored data contexts, we do not have access to the true values. If we were to use the same uncensored model on the censored data, we would anticipate that our parameter estimates will be biased. If we calculate point estimates for the mean and standard deviation, then we can see that we are likely to underestimate the mean and standard deviation for this particular dataset and censor bounds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean=12.32; std=3.76\n"
     ]
    }
   ],
   "source": [
    "print(f\"mean={np.mean(censored):.2f}; std={np.std(censored):.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [mu, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7a7573b864534afe8f44d92e9ef2d652",
       "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 1 seconds.\n"
     ]
    }
   ],
   "source": [
    "uncensored_model_2 = uncensored_model(censored)\n",
    "with uncensored_model_2:\n",
    "    idata = pm.sample()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, we see that both the mean and standard deviation are underestimated when using the uncensored model on censored data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x535.887 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = az.plot_dist(idata)\n",
    "az.add_lines(pc, {\"mu\": true_mu, \"sigma\": true_sigma});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Censored data models\n",
    "\n",
    "The models below show two approaches to dealing with censored data. First, we need to do a bit of data pre-processing to count the number of observations that are left or right censored. We also need to extract just the non-censored data that we observe."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(censored_data/model1)=\n",
    "### Model 1 - Imputed Censored Model of Censored Data\n",
    "\n",
    "In this model, we impute the censored values from the same distribution as the uncensored data. Sampling from the posterior generates possible uncensored data sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_right_censored = sum(censored >= high)\n",
    "n_left_censored = sum(censored <= low)\n",
    "n_observed = len(censored) - n_right_censored - n_left_censored\n",
    "uncensored = censored[(censored > low) & (censored < high)]\n",
    "assert len(uncensored) == n_observed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [mu, sigma, right_censored, left_censored]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9f2aeee34334e2abae2db5eff46aaac",
       "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 5 seconds.\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as imputed_censored_model:\n",
    "    mu = pm.Normal(\"mu\", mu=((high - low) / 2) + low, sigma=(high - low))\n",
    "    sigma = pm.HalfNormal(\"sigma\", sigma=(high - low) / 2.0)\n",
    "    right_censored = pm.Normal(\n",
    "        \"right_censored\",\n",
    "        mu,\n",
    "        sigma,\n",
    "        transform=pm.distributions.transforms.Interval(high, None),\n",
    "        shape=int(n_right_censored),\n",
    "        initval=np.full(n_right_censored, high + 1),\n",
    "    )\n",
    "    left_censored = pm.Normal(\n",
    "        \"left_censored\",\n",
    "        mu,\n",
    "        sigma,\n",
    "        transform=pm.distributions.transforms.Interval(None, low),\n",
    "        shape=int(n_left_censored),\n",
    "        initval=np.full(n_left_censored, low - 1),\n",
    "    )\n",
    "    observed = pm.Normal(\"observed\", mu=mu, sigma=sigma, observed=uncensored, shape=int(n_observed))\n",
    "    idata = pm.sample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAAY/B7afzz+seVYYq5pRHW8c/G0FBoBAPB0LpkwKt4wvzEx15fPx02P7ojWnr4UWgEAAAAXmuEuAACAp3G4ozu+tHV/Yu7SCfXxO42jU2gEADC4VJWVxj2XzYuR5aWJ2XXH2+KLW/al0AoAAAAAAAAunCMd3XHPE7sTc2WZTNxx8ZyoKk1+1wYAQHG9eeHUWDluZGLuUEd3fOixHZHNu8AQAAAAhjrDXQAAAE/jY0/uia5srt9MRUkmrl02MzKZTEqtAAAGl8m1VXHnxXOjkF9Lf73tQPzm8KmidwIAAAAAAIALIZfPxx1rdkZrbzYx+/ZFU2PuqNoUWgEAkKQ0k4k7L54ToyvLE7O/OXLaBYYAAAAwDBjuAgAA+C3+5eDJ+JdDyaMRr58/JabUVaXQCABg8Lp04qh4+6KpBWVvfXxnHOnoLnIjAAAAAAAASN93dh6ONcdaE3Mrx42M/zV3cgqNAAAo1Jiqirjz4jkFfZT7V08diJ8dOFH0TgAAAMCFY7gLAADgv+jsy8bH1u9JzE2rq4rXOCAHAFCQ185rjKsmNyTmzvT0xc2P7Yi+XD6FVgAAAAAAAJCO5rbO+Oym5sTciPLSuHXV7CjJZFJoBQDAuVg1vj7evLCwCwxvf3xn7G7tKHIjAAAA4EIx3AUAAPBffHnr/jjc0ZOYu375zKgo9WcVAEAhSjKZ+NCq2TG1rioxu+FEW/zF5pYUWgEAAAAAAEDx9eXycfvjO6O7gMtrrl8+MybUVKbQCgCAZ+L18xvj4vH1ibnObC6ufXhbtPb0pdAKAAAASJsvzAEAAP6DXWc64ps7DiXmXjx1bKwq4IUrAAD/rq68LO66ZG5UliTfDv7V7QfjN4dPpdAKAAAAAAAAiuvr2w/E5lPtibkXTxsbL5o6NoVGAAA8U6WZTNxx8ZyYWFORmN1/tis+9NiOyOaTB1wBAACAwcVwFwAAwP+Ty+fjnnW7E1+M1pWXxruXTE+pFQDA0DJ3VG28f1lTQdnb1+yKE109RW4EAAAAAAAAxbP99Nn44pb9ibmJNRVxbYHv0QAAuLAaKsvjnkvnFXSB4W+OnI4vbN6XQisAAAAgTYa7AAAA/p8fNh+L9SfaEnPvWDQtxlQl35AEAMBv90czxsfvFXBT+Knu3rj98Z2Rc+MkAAAAAAAAg1BPNhe3r9kZfQW877pl5eyoKy9LoRUAAOfD/Ia6+ODKWQVl/3rbgfjpgRNFbgQAAACkyXAXAABARJzs6o1Pb2xOzC1qqIuXzpyQQiMAgKErk8nEDStmxvS6qsTso0fPxDd3HEqhFQAAAAAAAJxfX966P3ae6UjMvXLWxFg1vj6FRgAAnE+/P21cvGr2pIKydzy+M3a3Jv82BAAAAAYHw10AAAAR8akNe6O1p6/fTElEXL9iZpRmMumUAgAYwmrKSuMjl86NypLk31af3dQSW062p9AKAAAAAAAAzo9NJ9viq9sOJOam1VXFOy+alkIjAACK4erF02PluJGJuc5sLq59eFvimXUAAABgcDDcBQAADHuPHD4d/7zveGLuFbMnxrxRtSk0AgAYHubU18b7ljYl5rL5fNzy2PZo73VoDQAAAAAAgIGvqy8btz++M3IJuZKI+NCq2VFVVppGLQAAiqCsJBMfuWRuTKypSMzuP9sVtzy2Pfpy+RSaAQAAAMVkuAsAABjWurK5uHvd7sTcuKryeOvCqSk0AgAYXl7aND6e3zg6Mbf/bHd8fP3e4hcCAAAAAACAZ+mzm1uipb0rMffaeY2xeMyIFBoBAFBMDZXlcc+l86KyJJOYfeTImfjUhr3FLwUAAAAUleEuAABgWPvOgdY41NGdmHvf0qaoKy9LoREAwPCSyWTixhWzCrpx8ofNx+In+0+k0AoAAAAAAACemTVHz8S3dx5OzM2ur4k3LZiSQiMAANIwv6EuPrhyVkHZ7+w6HH+3K/k3IwAAADBwGe4CAACGre76sfF/DrUl5q6Y1BC/0zg6hUYAAMPTyIqyuGP1nIL+wfrudbvjaGfy8CoAAAAAAACkrb23Lz68dldiriyTiVtXzY6KUp90AAAMJb8/bVy8avakgrIfW78nHj1yuriFAAAAgKLxlgcAABiW8pGJYyt+J3IJuZqykrh2WVNkMplUegEADFdLx46MNy+cmphr7emLO9fsilw+n0IrAAAAAAAAKNynNzTHoY7kS2jesnBKzB1Vm0IjAADSdvXi6bFy3MjEXDYfceOj22Nva2cKrQAAAIDzzXAXAAAwLJ2ZvSS6R09IzP35omkxoaYyhUYAALx+fmOsGJt8aO2xo2fiOzsPp9AIAAAAAAAACvPokdPxg71HE3OLGuri1XMbU2gEAMCFUFaSiY9cMjcmFXAGvb03G+9/eGuc6u5NoRkAAABwPhnuAgAAhp3e6ro4uejSxNyihrp42ayJKTQCACAiojSTiVtXz4668tLE7IObmmPXmY4UWgEAAAAAAED/zvZm464ndiXmKksy8aFVs6OsJJNCKwAALpSGyvK4//J5UVOW/AnvgbPdcc3DT0VXXzaFZgAAAMD5YrgLAAAYVvIRcXz58yJfVtFvrjQTccOKmVGacUgOACBNE2sq47rlMxNzPbl83Pb4jujN5VJoBQAAAAAAAE/vwU3NcbijJzH3joumx4yR1Sk0AgDgQptdXxt3Xjy3oI94N59sj1sf3xnZfL7ovQAAAIDzw3AXAAAwrJxtnB0dk5oSc/9rzuSYO6o2hUYAAPxXvzd1bPze1LGJue1nOuIvt+5PoREAAAAAAAD8dmuOnom/230kMbdi7Mh45eyJKTQCAGCgeO6khnj3khkFZX9+8GR8ekNzcQsBAAAA543hLgAAYNjIllfG8WVXJuYaayvjTQumpNAIAICnc+2ypphQXZGY+8q2A7HlZHsKjQAAAAAAAOA/6+jLxkfW7krMVZeWxC2rZkVJJpNCKwAABpJXzZ4YL20aX1D2WzsPxbd2HCpyIwAAAOB8MNwFAAAMGycvujyyVbWJueuXz4yqstIUGgEA8HRGVJTFratnR9KnC9l8xO1rdkZXNptKLwAAAAAAAPg3n93UEgc7uhNz77xoWkyurUqhEQAAA00mk4lrlzXF6nH1BeU/uWFv/GT/iSK3AgAAAJ4tw10AAMCw0DlmcrTOvCgx9/vTxsYlE0YVvxAAAIlWjquPV8+dnJjb29YZf7F5XwqNAAAAAAAA4F89cexM/O2uw4m55WNHxMtmTUyhEQAAA1VZSUl89NK5MXNkdWI2HxG3Pr4j1hw9U/xiAAAAwDNmuAsAABjy8iUlcWzF8xNz9RVl8Z4lM4pfCACAgr114dSCDqz9zY5Dse54awqNAAAAAAAAGO66+rLxkbW7EnOVpSVx08pZUZLJpNAKAICBbERFWXziOQtibFV5YrY3l49rf7Mttp0+m0IzAAAA4Jkw3AUAAAx5p+aujN6RoxNz710yIxoqk1+EAgCQnorSkrh11ewoTfiYIR8Rd67ZGZ192XSKAQAAAAAAMGx9bvO+2H+2OzH3jkXTYmpd8iU1AAAMDxNrKuPjz1kQNWXJn/Z29GXjPb/aGvvbu1JoBgAAAJwrw10AAMCQ1jOiIU7NX52YWz2uPn5/2tgUGgEAcK7mN9TFGxc0JuYOnO2Oz2/el0IjAAAAAAAAhqv1x1vj2zsPJeaWjBkRr5w9MYVGAAAMJvNG1cZdl8yN0v7vMYyIiFPdvfHuX22J4509xS8GAAAAnBPDXQAAwJCVy+fj2PLnR5SW9purLMnE9SuaIpMp4O0nAAAXxOvnNcb8UbWJuW/vPBQbTrSl0AgAAAAAAIDhpiubjQ+v3RX5hFxlSSZuWTkrSpxHAgDgt7hsYkNcv3xmQdkDZ7vj3b/aEme6e4vcCgAAADgXhrsAAIAh66fHzkbXuMbE3BsXTI2pddUpNAIA4JkqKymJW1fPjoqS/j9uyEfEh9fsjK5sNp1iAAAAAAAADBtf2LwvWtq7EnNvWzQtpo1wHgkAgKf3R00T4m0LpxaU3dXaGe/99dZo7+0rcisAAACgUIa7AACAIelEV098teV0Ym5adXm8eu6k4hcCAOBZmzmyJt62aFpirrm9K768ZX8KjQAAAAAAABguNp9si7/ZcSgxd9HounjVHOeRAABI9ob5jfHymRMKym45dTY+8PBT0dXnQkMAAAAYCDL5fD5/oUsAAACcbzc8si1+duBkv5lMRHzm0tmxqnFcOqUAAHjWsvl8vOXnm2LzyfZ+cyUR8eXnL46Fo+vSKQYAAAAAAMCQ1ZvLxet+siF2tXb2m6soycRXX7AkmkbWpNRsaOjo6IgNGzb0m1myZEnU1Pj/CgAMPdl8Pm55dEf85MCJgvKXTRgV910+L8pLSorcDAAAAOiP4S4AAGDI+emBE/HBR7Yn5l4xa2J8YFlTCo0AADifdrd2xGt/siF6c/3/8/askdXxlRcscUgNAAAAAACAZ+XLW/fHF7bsS8y986Jp8dp5jSk0AgBgKOnJ5uJ9v94aa461FpS/anJD3HXJ3ChzLgoAAAAuGH+VAwAAQ8qZnt64b92exNy46op4+6KpKTQCAOB8mzmyJt68IPm33K7WzvjG9oMpNAIAAAAAAGCo2tPaEX/11P7E3MKG2vizOZNTaAQAwFBTUVoS91w2LxY01BaU/8XBU3HzYzuiL5crcjMAAADg6RjuAgAAhpRPbWiOk929iblrlzVFXXlZCo0AACiGV8+dFPNGJR9U+/LW/bGvvTOFRgAAAAAAAAw1uXw+7npid/Tm8v3myjKZuGXV7CgryaTUDACAoaauvCw+9ZwFMXNkdUH5nx04GR96bGf0JfxWBQAAAIrDcBcAADBkPHL4dPyw+Vhi7vmNo+OqyaNTaAQAQLGUlZTELatmRWmm/48fenL5uOeJPZHPO6AGAAAAAADAufm7XYdjw4m2xNwb5jfGzJE1KTQCAGAoq68sjweeuzCm1FYWlP/JgRNx2+M7jHcBAADABWC4CwAAGBLO9mbjo+t2JeZGlpfGtcuaUmgEAECxzamvjTfMb0zMPX7sTPxTy/EUGgEAAAAAADBUHO7ojs9ubknMzRxZHa8r4J0VAAAUYmx1RTxwxcIYX11RUP7H+0/E7WuMdwEAAEDaDHcBAABDwuc2t8Thjp7E3HuXzogxVYW9xAQAYOB7/fzGaBpRnZj71Ia9caa7N4VGAAAAAAAADHb5fD7ufmJ3dPTl+s1lIuLGFbOivMSnGQAAnD+Ta6viM1csjIbK8oLyP9p3Im5+bHv05vr//QoAAACcP94OAQAAg96Tx1vju7sOJ+YunVAffzBtXAqNAABIS3lJSdywYmZi7nRPX3x6Y3MKjQAAAAAAABjs/u++4/GbI6cTc6+cPTEWjxlR/EIAAAw700dUx4NXLIxRFWUF5X924GTc8Jvt0Z013gUAAABpMNwFAAAMat3ZXNy1dlfkE3I1ZSVxw/JZkclkUukFAEB6lo0dGS9tGp+Y+4fmY7H22JkUGgEAAAAAADBYnerujY+v35uYm1RTGW9fNK34hQAAGLZm1dfEZ65cGPUFjnf96vCpuPbhp6KrL1vkZgAAAIDhLgAAYFD78tb90dzelZh7x0XTY1JtZQqNAAC4EN550fQYXVmemLv7id1ulQQAAAAAAOBpfXz9njjT05eYu2HFzKgpK02hEQAAw9mc+tr4zBULY2R5Yb89Hz16Jt77663R3pv8mxYAAAB45gx3AQAAg9ZTp9rj69sPJOaWjhkRL5s5IYVGAABcKCMryuJ9S2ck5lrau+Kr25J/QwIAAAAAADD8/OrQqfjRvhOJuZdMHxeXThhV/EIAABARc0fVxgNXLIwRBY53rTveFu/4ly1xsqu3yM0AAABg+DLcBQAADEp9uVx8ZO2uyOb7z1WUZOKmlbOiJJNJpxgAABfMi6aMicsK+EDiK9sOxN7WzuIXAgAAAAAAYNBo7+2Le9btTsw1VJbHe5ZMT6ERAAD8u/kNdfGZKxbGyIqygvLbTp+Nt/1iUxzu6C5yMwAAABieDHcBAACD0te3H4ztZzoSc29eODWmj6hOoREAABdaJpOJ65Y3RWVp///03ZvLx93rdkUun7ACCwAAAAAAwLDx2U0tcbSzJzH3gWUzor6iPIVGAADwn81vqIvPXrkwGioLG+9qae+Kt/x8U+xpTT53DwAAAJybTD7vyyQAAGBw2dvaGa/+yfrozfX/58yckdXx53WdUZrJPG1myZIlUVNTc74rAgBwAX1t24H4zKaWxNxNK2bGHzZNSKERAAAAAAAAA9mTx1vjbb/YnJi7YlJD3HfZvMj0cx6Jc9fR0REbNmzoN+OcFwDAv9vT2hHv+uWWON7VW1C+vqIs7r98fiwZM6LIzQAAAGD4MNwFAAAMKrl8Pt72i82x4URbv7nSTCbuWTQ+Pnf7zf3m7r333pgyZcr5rAgAwAXWl8vF6366MXae6f+myJHlpfHt310eo6vciA4AAAAAADBcdWdz8ZqH1kdze1e/udqy0vjW7y6N8dWVKTUbPvbv3x/XXXddvxnnvAAA/rOWts545y+3xNHOnoLylSWZuOPiOfG8xjFFbgYAAADDQ8mFLgAAAHAuvrvrcOJoV0TEa+dNjqbaihQaAQAw0JSVlMSNK2ZG0j3nrb3ZeGBjcyqdAAAAAAAAGJj+6qn9iaNdERHvWjzdaBcAAAPGtBHV8RdXLYoptVUF5btz+bjhke3xt7sOF7kZAAAADA+GuwAAgEHj4Nmu+OymlsTcjBHV8Yb5blcEABjOFo0eES+fNTEx948txwoahgUAAAAAAGDo2XHmbHx128HE3PKxI+KlTeNTaAQAAIWbXFsVX3jeophTX1NQPh8R9z+5Jx7Y2By5fL645QAAAGCIM9wFAAAMCvl8Pj76xO7ozOb6zWUi4qaVs6Ky1J87AADD3dsXTY1xVeWJufuf3BNZB9EAAAAAAACGlb5cPj6ydlfie6KKkkzcuGJWlGQyKTUDAIDCjamqiM9duSiWjBlR8DNf334wPvjI9ujsyxaxGQAAAAxtvmQHAAAGhR82H4vHjp5JzL1i1sRzeukIAMDQVVdeFtcsa0rMbTt9Nv737iMpNAIAAAAAAGCg+PbOQ7H11NnE3JsXTo1pI6pTaAQAAM/MiIqyeOC5C+KyCaMKfubnB0/G23+xOY519hSvGAAAAAxhhrsAAIAB72hnd3xiw97E3KSayvjzi6YVvxAAAIPG8yaPjismNSTmPr+5JU5396bQCAAAAAAAgAttf3tX/MWWfYm5ufU18b/mTEqhEQAAPDtVZaVx/+Xz4g+mjSv4madOn403/GxjPHWqvYjNAAAAYGgy3AUAAAxo+Xw+7n5id7T3ZhOzH1wxM2rKSlNoBQDAYJHJZOJ9S2ZERUmm31xrbzY+t7klpVYAAAAAAABcKPl8Pj76xK7ozub6zZVmIm5aOSvKSnx2AQDA4FBWUhIfWjUr3jC/seBnjnX2xNt+sTke2n+8iM0AAABg6PEGCQAAGND+seVY/Prw6cTc/5gxLi6ZMKrofQAAGHwa66riNfOSD6P9YM/R2Or2SAAAAAAAgCHt/zQfizXHWhNzfzZncsxvqEuhEQAAnD+ZTCbevmhaXL98ZsEfEHdlc3HTozvis5taIpvPF7UfAAAADBWGuwAAgAHraGd3fHz93sTcmKryePfiGUXvAwDA4PXauZNjUk1lv5l8RNz35J7IOXwGAAAAAAAwJB3v7IlPbdibmJtSWxVvXjil+IUAAKBI/mTmhLjv8vlRVVr4Z8Rf2XYgPvDwU9HW01fEZgAAADA0GO4CAAAGpHw+H3c/sTvae7OJ2euXzYyRFWUptAIAYLCqKiuN9y6ZnpjbfLI9fth8LIVGAAAAAAAApO2+J/cUdB7pxpUzo6q0NIVGAABQPM+d1BCfv2pRjK0qL/iZhw+fjjf+bGPsPHO2iM0AAABg8DPcBQAADEj/2HIsfn34dGLud6eOiasaRxe/EAAAg95Vk0fHJePrE3MPbmqOVrdGAgAAAAAADCk/O3Aifn7wZGLuj2aMj5Xjkt8pAQDAYLCgoS7+8vmLY96o2oKfaWnvijf+bFP8w96jRWwGAAAAg5vhLgAAYMA52tkdH1+/NzE3urI8PrC0qfiFAAAYEjKZTFyzrCnKMpl+c6e6++KLW/al1AoAAAAAAIBia+3pi/ue3JOYG1dVHlcvnp5CIwAASM+Emsr4/FWL4spJDQU/053NxZ1rd8Wda3ZGV1+2iO0AAABgcDLcBQAADCj5fD4++sTuaO9Nfrl3w/KZUV9ZnkIrAACGiukjquPP5kxKzH131+HYceZsCo0AAAAAAAAotgc2NseJrt7E3LXLZ8aIirIUGgEAQLpqykrjnsvmxWvnTj6n5/6h+Vi88Wcbo7mts0jNAAAAYHAy3AUAAAwoP2w+Fg8fPp2Y+72pY+OqxtHFLwQAwJDzhgVTYlxV/wOwuYi4/8k9kc/n0ykFAAAAAABAUaw5eib+fu/RxNwLGsfEVZOdRwIAYOgqyWTinYunxx0Xz4nK0sI/L97V2hmv/+mG+L/7jhexHQAAAAwuhrsAAIAB42hnd3xiw97E3OjK8rhm6Yyi9wEAYGiqKSuNdy+ZkZh78nhb/MhhMwAAAAAAgEGrqy8bdz2xKzE3srw0rlk2o/iFAABgAPi9qWPji8+7KCbWVBT8TEdfLj702I6454nd0Z3NFbEdAAAADA6GuwAAgAEhn8/HR5/YHe292cTsDctnRn1leQqtAAAYql40ZUysGDsyMffpjc3R0Zf8GxUAAAAAAICB5wtb9sWBs92JufcsmRFjqgofLQAAgMFu3qja+OvfWVLQGar/6Ht7jsRbfr4p9rV3FqkZAAAADA6GuwAAgAHhh83H4uHDpxNzvzd1bFzVOLr4hQAAGNIymUx8YFlTlGb6zx3v6o2vbjuQTikAAAAAAADOm62n2uNvdhxKzF08vj5eMn1cCo0AAGBgaagsjweuWBCvmTv5nJ7bdvpsvOahDfH3e45EPp8vUjsAAAAY2Ax3AQAAF9zRzu74xIa9ibnRleVxzdIZRe8DAMDwMKu+Jl4xa1Ji7pvbD8bhjuSb2AEAAAAAABgY+nK5+PDaXZFLyFWVlsQHV8yMTCbhthcAABiiykpK4l2Lp8f9l82LkeWlBT/Xmc3FR57YHTc8sj1Od/cWsSEAAAAMTIa7AACACyqfz8dda3dHe282MXvDiplRX1meQisAAIaLtyycEg0JvzG7c/l4cFNzSo0AAAAAAAB4tr6+/WDsPNORmHv7oqkxubYqhUYAADCwXTF5dHzlBUtiYUPtOT3384Mn488eWh+PHD5dnGIAAAAwQBnuAgAALqgfNh+L3xw5nZh78dSxcdXk0cUvBADAsFJXXhbvumhaYu5H+07ExhNtKTQCAAAAAADg2Whu64wvb92fmFvUUBevnD0phUYAADA4TK6tii8876J45ayJ5/Tcia7eeM+vt8bHntwTXdnkC70BAABgKDDcBQAAXDBHO7vjExv2JuZGV5bH+5fOKHofAACGpz+YPi7mj0q+KfITG/ZGLp9PoREAAAAAAADPRC6fj4+s3RU9uf7f6ZRmMnHjyplRmsmk1AwAAAaH8pKSuGZZU9x1ydyoKSs9p2e/s+twvP4nG2P76bNFagcAAAADh+EuAADggsjn83HX2t3R3pt8o84NK2ZGfWV5Cq0AABiOSjKZeG8BQ7GbT7bHj/YdL34hAAAAAAAAnpHv7T4S60+0JeZeN29yzK5PvtgFAACGqxdMGRNffcHimFtfc07P7WnrjDf8dGN8bduByLokEQAAgCHMcBcAAHBB/EPzsfjNkdOJuRdPHRtXTR5d/EIAAAxry8eOjBc0jknMPbipJbr6ksdnAQAAAAAASNeRju54cFNzYm7GiOp4w/wpKTQCAIDBbWpddXzp+YvjZTMnnNNzffl8fGZTS7z155tib2tnkdoBAADAhWW4CwAASN2Rju745Ia9ibkxVeXx/mUzit4HAAA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",
      "text/plain": [
       "<Figure size 2400x535.887 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = az.plot_dist(idata, var_names=[\"mu\", \"sigma\"])\n",
    "az.add_lines(pc, {\"mu\": true_mu, \"sigma\": true_sigma});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the bias in the estimates of the mean and standard deviation (present in the uncensored model) have been largely removed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model 2 - Unimputed Censored Model of Censored Data\n",
    "\n",
    "Here we can make use of `pm.Censored`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [mu, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "08f96e12e09046ca98530535b0d7b719",
       "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 3 seconds.\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as unimputed_censored_model:\n",
    "    mu = pm.Normal(\"mu\", mu=0.0, sigma=(high - low) / 2.0)\n",
    "    sigma = pm.HalfNormal(\"sigma\", sigma=(high - low) / 2.0)\n",
    "    y_latent = pm.Normal.dist(mu=mu, sigma=sigma)\n",
    "    obs = pm.Censored(\"obs\", y_latent, lower=low, upper=high, observed=censored)\n",
    "    idata = pm.sample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x535.887 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = az.plot_dist(idata, var_names=[\"mu\", \"sigma\"])\n",
    "az.add_lines(pc, {\"mu\": true_mu, \"sigma\": true_sigma});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, the bias in the estimates of the mean and variance (present in the uncensored model) have been largely removed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion\n",
    "\n",
    "As we can see, both censored models appear to capture the mean and variance of the underlying distribution as well as the uncensored model! In addition, the imputed censored model is capable of generating data sets of censored values (sample from the posteriors of `left_censored` and `right_censored` to generate them), while the unimputed censored model scales much better with more censored data, and converges faster."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n",
    "\n",
    "- Originally authored by [Luis Mario Domenzain](https://github.com/domenzain) on Mar 7, 2017.\n",
    "- Updated by [George Ho](https://github.com/eigenfoo) on Jul 14, 2018.\n",
    "- Updated by [Benjamin Vincent](https://github.com/drbenvincent) in May 2021.\n",
    "- Updated by [Benjamin Vincent](https://github.com/drbenvincent) in May 2022.\n",
    "- Updated by [Osvaldo Martin](https://github.com/aloctavodia) in Dec 2025."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Thu Dec 11 2025\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.13.5\n",
      "IPython version      : 9.3.0\n",
      "\n",
      "pytensor: 2.35.1\n",
      "aeppl   : not installed\n",
      "\n",
      "numpy     : 2.2.6\n",
      "matplotlib: 3.10.3\n",
      "pymc      : 5.26.1\n",
      "arviz     : 0.23.0.dev0\n",
      "\n",
      "Watermark: 2.5.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w -p pytensor,aeppl"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{include} ../page_footer.md\n",
    ":::"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:base] *",
   "language": "python",
   "name": "conda-base-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  },
  "vscode": {
   "interpreter": {
    "hash": "970ac73df0f14d7a1f980febd250c4ded990984ec0e2432b12dcbf556b464244"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}