lectures/L09_bayesian.ipynb

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    "# Bayesian Statistical Inference: II\n",
    "\n",
    "*Davide Gerosa (Milano-Bicocca)* \n",
    "\n",
    "##### Reading:\n",
    "\n",
    "- [Textbook](http://press.princeton.edu/titles/10159.html) Chapter 5.\n",
    "- [Jake VanderPlas's blog \"Frequentism and Bayesianism: A Practical Introduction\"](http://jakevdp.github.io/blog/2014/03/11/frequentism-and-bayesianism-a-practical-intro/)\n",
    "- [Jake VanderPlas: \"Frequentism and Bayesianism: A Python-driven Primer\"](https://arxiv.org/abs/1411.5018)\n",
    "- [Hogg, Bovy and Lang: \"Data analysis recipes: Fitting a model to data\"](https://arxiv.org/abs/1008.4686)\n",
    "\n",
    "\n",
    "##### For those who want to dive deep:\n",
    "\n",
    "- [Jake VanderPlas's workshop \"Bayesian Astronomy\"](https://github.com/jakevdp/BayesianAstronomy)\n",
    "- [D. Sivia and J. Skilling: \"Data Analysis: A Bayesian Tutorial\"](https://www.amazon.com/Data-Analysis-Bayesian-Devinderjit-Sivia/dp/0198568320)\n",
    "- [E.T. Jaynes: \"Probability Theory: The Logic of Science\"](http://bayes.wustl.edu/etj/prob/book.pdf)\n",
    "- [E.T. Jaynes: \"Confidence Intervals vs. Bayesian intervals\"](http://bayes.wustl.edu/etj/articles/confidence.pdf)\n",
    "- [This great explanation of confidence levels versus credible regions on Stackexchange](https://stats.stackexchange.com/questions/2272/whats-the-difference-between-a-confidence-interval-and-a-credible-interval/2287#2287)\n",
    "\n",
    "\n",
    "\n",
    "This course is based on previous work by many people. See [here]((https://github.com/dgerosa/astrostatistics_bicocca_2024/blob/main/README.md) for credits.\n"
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    "## Simple parameter estimation examples <a class=\"anchor\" id=\"one\"></a>\n",
    "\n",
    "### Underlying Gaussian distribution with heteroscedastic Gaussian uncertainties <a class=\"anchor\" id=\"onea\"></a>\n",
    "\n",
    "The final example we saw in the previous lecture dealt with Bayesian parameter estimation of a Gaussian distribution, for $\\mu$ and $\\sigma$. **But what if the values we measure $\\{x_i\\}$ also have a measurement uncertainty?** Crucially, we're dealing with two levels of spread then:\n",
    "\n",
    "- the underlying distribution spread, $\\sigma$, and \n",
    "- the measurement uncertainties of the data, $\\{e_i\\}$\n",
    "\n",
    "The measurement uncertainties further blur the underlying distribution. In fact, if the uncertainties are homoscedastic, the distribution of $\\{x_i\\}$ will be Gaussian, ***BUT*** **if the uncertainties are heteroscedastic the distribution of $\\{x_i\\}$ will be non-Gaussian!**\n",
    "\n",
    "- The figure below shows a distribution of $10^6$ points drawn from $\\mathcal{N}(0,1)$ and sampled with heteroscedastic Gaussian errors with widths, $e_i$, uniformly distributed between $0$ and $3$. \n",
    "- A linear superposition of these Gaussian distributions with widths equal to $\\sqrt{1 + e_i^2}$ results in a non-Gaussian distribution. \n",
    "- The best-fit Gaussians centered on the sample median with widths equal to sample standard deviation and quartile-based $\\sigma_G$ are shown for comparison.\n",
    "\n",
    "![](https://www.astroml.org/_images/fig_distribution_gaussgauss_1.png)"
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    "We're trying to find the $\\mu$ and $\\sigma$ parameters of the underlying distribution. With uniform priors on each, the log-posterior pdf can be written as\n",
    "\n",
    "$$ \\ln p = \\mathrm{constant} - \\frac{1}{2}\\sum_{i=1}^N \\left( \\ln(\\sigma^2+e_i^2) + \\frac{(x_i-\\mu)^2}{(\\sigma^2+e_i^2)} \\right), $$\n",
    "\n",
    "which looks identical to the log-likelihood $\\ln L$ up to a constant due to the uniform priors. We can actually analytically maximize this to find the MAP (maximum a posteriori) value of $\\mu_0$,\n",
    "\n",
    "$$ \\mu_0 = \\frac{\\sum_{i=1}^N x_i / (\\sigma_0^2 + e_i^2)}{\\sum_{i=1}^N 1 / (\\sigma_0^2 + e_i^2)} $$\n",
    "\n",
    "but a closed-form analytic solution for $\\sigma_0$ does not exist. \n",
    "\n",
    "So we resort to numerical methods and just plot $\\ln p$ on a grid. (Pause here for a sec and think about this: we *numerically* explore a *grid* of values)\n",
    "\n",
    "The following to produces the log-posterior pdf of parameters $\\mu$ and $\\sigma$ of an underlying Gaussian distribution. The dataset has $N=10$ values, drawn from $\\mu=1$, $\\sigma=1$, each measured with an uncertainty drawn from a uniform distribution $0<e_i<3$."
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      "/Users/dgerosa/box/lib/python3.11/site-packages/astroML/linear_model/linear_regression_errors.py:10: UserWarning: LinearRegressionwithErrors requires PyMC3 to be installed\n",
      "  warnings.warn('LinearRegressionwithErrors requires PyMC3 to be installed')\n"
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      "text/plain": [
       "<Figure size 1000x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 648,
       "width": 802
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Execute this cell\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format='retina'\n",
    "\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from scipy.stats import norm\n",
    "#np.random.seed(42)\n",
    "\n",
    "\"\"\"\n",
    "Gaussian Distribution with Gaussian Errors\n",
    "------------------------------------------\n",
    "Figure 5.7\n",
    "\n",
    "The logarithm of the posterior probability density function for :math:`\\mu`\n",
    "and :math:`\\sigma`, :math:`L_p(\\mu,\\sigma)`, for a Gaussian distribution with\n",
    "heteroscedastic Gaussian measurement errors (sampled uniformly from the 0-3\n",
    "interval), given by eq. 5.64. The input values are :math:`\\mu = 1` and\n",
    ":math:`\\sigma = 1`, and a randomly generated sample has 10 points. Note that\n",
    "the posterior pdf is not symmetric with respect to the :math:`\\mu = 1` line,\n",
    "and that the outermost contour, which encloses the region that contains 0.997\n",
    "of the cumulative (integrated) posterior probability, allows solutions with\n",
    ":math:`\\sigma = 0`.\n",
    "\"\"\"\n",
    "# Author: Jake VanderPlas\n",
    "# License: BSD\n",
    "#   The figure produced by this code is published in the textbook\n",
    "#   \"Statistics, Data Mining, and Machine Learning in Astronomy\" (2013)\n",
    "#   For more information, see http://astroML.github.com\n",
    "#   To report a bug or issue, use the following forum:\n",
    "#    https://groups.google.com/forum/#!forum/astroml-general\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from astroML.plotting.mcmc import convert_to_stdev\n",
    "\n",
    "#----------------------------------------------------------------------\n",
    "# This function adjusts matplotlib settings for a uniform feel in the textbook.\n",
    "# Note that with usetex=True, fonts are rendered with LaTeX.  This may\n",
    "# result in an error if LaTeX is not installed on your system.  In that case,\n",
    "# you can set usetex to False.\n",
    "if \"setup_text_plots\" not in globals():\n",
    "    from astroML.plotting import setup_text_plots\n",
    "setup_text_plots(fontsize=13, usetex=False)\n",
    "\n",
    "np.random.seed(42)\n",
    "#np.random.seed(4211)\n",
    "\n",
    "def gaussgauss_logL(xi, ei, mu, sigma):\n",
    "    \"\"\"Equation 5.63: gaussian likelihood with gaussian errors\"\"\"\n",
    "    ndim = len(np.broadcast(sigma, mu).shape)\n",
    "\n",
    "    xi = xi.reshape(xi.shape + tuple(ndim * [1]))\n",
    "    ei = ei.reshape(ei.shape + tuple(ndim * [1]))\n",
    "\n",
    "    s2_e2 = sigma ** 2 + ei ** 2\n",
    "    return -0.5 * np.sum(np.log(s2_e2) + (xi - mu) ** 2 / s2_e2, 0)\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# Define the grid and compute logL\n",
    "#np.random.seed(5)\n",
    "mu_true = 1.\n",
    "sigma_true = 1.\n",
    "N = 10\n",
    "ei = 3 * np.random.random(N)\n",
    "xi = np.random.normal(mu_true, np.sqrt(sigma_true ** 2 + ei ** 2))\n",
    "\n",
    "sigma = np.linspace(0.01, 5, 70)\n",
    "mu = np.linspace(-3, 5, 70)\n",
    "\n",
    "logL = gaussgauss_logL(xi, ei, mu, sigma[:, np.newaxis])\n",
    "logL -= logL.max()\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# plot the results\n",
    "fig = plt.figure(figsize=(10, 7.5))\n",
    "plt.imshow(logL, origin='lower',\n",
    "           extent=(mu[0], mu[-1], sigma[0], sigma[-1]),\n",
    "           cmap=plt.cm.binary,\n",
    "           aspect='auto')\n",
    "plt.colorbar().set_label(r'$\\log(L)$')\n",
    "plt.clim(-5, 0)\n",
    "\n",
    "plt.text(0.5, 0.93,\n",
    "         (r'$L(\\mu,\\sigma)\\ \\mathrm{for}\\ \\mu_{\\rm true}=1,\\ '\n",
    "          r'\\sigma_{\\rm true}=1,\\ n=10$'),\n",
    "         bbox=dict(ec='k', fc='w', alpha=0.9),\n",
    "         ha='center', va='center', transform=plt.gca().transAxes)\n",
    "\n",
    "plt.contour(mu, sigma, convert_to_stdev(logL),\n",
    "            levels=(0.683, 0.955, 0.997),\n",
    "            colors='k')\n",
    "\n",
    "plt.axhline(mu_true,c='red',ls='dotted')\n",
    "plt.axvline(sigma_true,c='red',ls='dotted')\n",
    "\n",
    "plt.xlabel(r'$\\mu$')\n",
    "plt.ylabel(r'$\\sigma$')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Key takeaways**\n",
    "- By eye,  $\\mu=1$, $\\sigma=1$ are not too far from the MAP parameter values. This is ok, but...\n",
    "- The posterior pdf is not symmetric around $\\mu=1$.\n",
    "- In fact it is consistent within the $99.7\\%$ credible region of having $\\sigma=0$!. \n",
    "- The marginal distributions of each parameter would not look Gaussian either.\n",
    "\n",
    "\n",
    "Now try changing the random seed, explain what's going one... Also try changing the number of datapoints as well as the maximum value of $e_i$.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Gaussian distribution embedded in a uniform background distribution <a class=\"anchor\" id=\"oneb\"></a>\n",
    "\n",
    "What if we wanted to **model the mixture of a Gauassian distribution with a uniform distribution**. Goign outside of astronomy for a second, this is the typical scenario for particle physicists looking for new particles. The following is from the [Atlas bulletin](https://atlas.cern/updates/feature/higgs-boson) of July 4th, 2018, showing the Higgs boson peak embdded in background noise and other particles.\n",
    "\n",
    "![Atlas Higgs Boson Example](https://cds.cern.ch/record/2627611/files/Higgsto4l.png?subformat=icon-640)\n",
    "\n",
    "Obviously this isn't *exactly* a Gaussian and a uniform distribution, but a line feature superimposed upon a background is the sort of thing that a physicist or astronomer might see and is pretty close to this case for a local region around the feature of interest. \n",
    "\n",
    "Q: Any more examples of similar problems in your research areas?\n",
    "\n",
    "Let's assume that \n",
    "- the location parameter, $\\mu$, is known (say from theory) and\n",
    "- the uncertainties in $x_i$ are negligible compared to $\\sigma$.\n",
    "\n",
    "The likelihood of obtaining a single measurement, $x_i$, can be written as a probabilistic mixture of *either* the Gaussian *or* the uniform distribution. Hence, we use the **OR Rule** of probability:\n",
    "\n",
    "$$p(x_i|A,\\mu,\\sigma,I) = \\frac{A}{\\sigma\\sqrt{2\\pi}} \\exp\\left(\\frac{-(x_i-\\mu)^2}{2\\sigma^2}\\right) + \\frac{1-A}{W}.$$\n",
    "\n",
    "- Here the background probability is taken to be $0 < x < W$ and 0 otherwise.  \n",
    "- The feature of interest lies between $0$ and $W$.  \n",
    "- $A$ and $1-A$ are the relative strengths of the two components, which are obviously anti-correlated.  \n",
    "- Note that there will be covariance between $A$ and $\\sigma$. \n",
    "\n",
    "If we adopt a uniform prior in both $A$ and $\\sigma$:\n",
    "\n",
    "$$p(A,\\sigma|I) = C, \\; {\\rm for} \\; 0\\le A<A_{\\rm max} \\; {\\rm and} \\; 0 \\le \\sigma \\le \\sigma_{\\rm max},$$\n",
    "\n",
    "then the posterior pdf is given by\n",
    "\n",
    "$$\\ln [p(A,\\sigma|\\{x_i\\},\\mu,W)] \\propto \\sum_{i=1}^N \\ln \\left[\\frac{A}{\\sigma \\sqrt{2\\pi}} \\exp\\left( \\frac{-(x_i-\\mu)^2}{2\\sigma^2} \\right)  + \\frac{1-A}{W} \\right].$$\n",
    "\n",
    "The example below is for $200$ data points with $A=0.5, \\sigma=1, \\mu=5, W=10$. Specifically, the bottom panel is a result drawn from this distribution and the top panel is the likelihood distribution derived from the data in the bottom panel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rVsyw3c6dO3X16lVzv0OHDm7136FDBzPESp2COf17qjf7Ts+b74UAAOSX1BHzdmTX6wZSMcUiAAAFXNqALCwsLEc3bdPbsGGDy9RjaddKyc7WrVt19913myGMn5+fnnvuOZ08eVLbtm3TsmXLtHXrVh08eFDdunVzObdNmzb68ssvza+uXbvm+hrc9ccff+jXX3+V9O9N8BdffNHl+02bNjW3z58/n+U0WBlJ+7NLSEjQX3/9lfti08nN87R8+XKX/fz4GUv/hp0ff/yx9uzZowsXLmjjxo1atmyZVqxYod27d+v48eN64YUXzEBgy5Yteumll/KltvSmTJliBlr+/v6aOHGizpw5o+3btysiIkJ//vmnNm7cqAsXLmjnzp2aOHGirrvuOq/3VdhNmTJFq1atUrly5fTNN9/o5MmTioyMVGRkpGJiYvTNN9+Ya9mlpKRo+PDhLmsj5VRcXJx69+5thmM+Pj769NNPswzHFi5c6BKOpQY+x48f18qVK7VmzRqdOnVKU6dOVZkyZfT9999rwYIFbtWzfv16Pf300+Z+pUqV9Msvv+jEiRNauXKl1q5dq1OnTumDDz5QQECAZs6c6XbfVkobkF26dEn333+/fHx89OKLL+rkyZPasWOHIiIiFB0drejoaJffUxs2bMjVyNzCzul0ukwzWLlyZdWuXTvDtjt27HDZr1evnluPkb5ddHR0vvadnjffCwEAAABvIyADAKAAS0pKchmhktfpFdOuA1WxYkWFhoa6dV5ycrKGDBlirm8VEBCgefPmaeLEiQoJCXFpW716dc2dO9dleq29e/dq8ODBGj58uIYPH67g4OA8XUd2HA6HxowZY+6//fbbKlWqlEub9Gt65fRmbtmyZV1GpOVkja3s5OZ5SntOqVKl1LhxY4/Vk5mhQ4dq06ZNGjNmjOrWrZthm0qVKumdd97Rd999Zx774osvdP78ea/Xl968efPM7WeffVbPPfecSpcunWHbhg0b6rnnntPu3bsznBLRk30VdrGxsQoMDDTXpUob4vv7++vBBx/UokWLzKna4uPjrxltlZPH6tKli37//XdJ//4umjNnjh5//PFMz3E6nRo9erS5X6VKFa1cuVLdu3d3+cRssWLF9PDDD2vhwoXy9/d3ey2tJ554whw1GxQUpOXLl6tv377y8fm//2oVL15cTz31lGbNmiXDMArFOl1pA7LTp0+rdOnSWrlypd5+++1rRkXVq1dPP/74o8vPMzcjcw8ePOj2WpY5/Uo7Fae3fP/999q3b5+5f//992f6qez0H8qoUaOGW49Rs2ZNl/0DBw7ka9/pefO9EAAAAPA2AjIAAAqw7du3u6yVk9eALO2nwTMLNDLy+eefu9zs/Pzzz3X77bdn2r548eJ64oknzP3z58+73Gz1tk8//dS81latWmW4JkqNGjVc1sLKzWiHtD/DtEFmXuXmeUp7w71y5couN+e9JX3omJV7771XN954oyTpypUrWrx4sbfKytSRI0fM7Y4dO7p1jo+PT4Y3uD3ZV1HwzDPPqF27dpl+v127di6jrBYsWJDjUZv79+9Xhw4dzKn7goKCtHTpUvXv3z/L85YuXeoyYu2DDz5QtWrVMm1/44036sknn3Srpg0bNrgEAm+++aYaNGiQafs+ffrkeXrJ/OB0Ol1+5/v4+OjXX3/N8jmuUaOG6tSpY+6nHQVrB0ePHnX5YEa5cuX0wgsvZNo+/dpkqaMss5N+DcfUD67kV98Z8dZ7IQAAAOBtBX/yewAAbCzt9IpS3gOytJ8Gr1q1qlvnOJ1OffTRR+Z+ly5d9NBDD2V7XqdOnVz2//nnH7Vv397NSnMvNjZWb7zxhrn/0UcfZRoWNW3aVJGRkZJyF5Clvcme05v9WcnN83T27FlzO/1NzsysXr1ab731VrbtFi1a5FZ/2bnhhhvM6bfWr1+vgQMHeqRfd6Vd9+zvv/9Wjx49CkRfhZ2vr69LIJ6Zxx9/XO+++66Sk5OVkpKiX3/91e2RZFFRUbrjjjt06tQpSf/+3Vu0aJFbazL+9ttv5nZISIjuvvvubM959NFH9eGHH2bb7pdffjG3S5Ys6dbvxtGjR2vmzJnZtrPSnj17XAKuhx56SJ07d872vLS/a939PZRW8eLF1b179xyf546cfCgkp+Li4tSvXz+dOXPGPDZlyhSVL18+03PSB4jursuYvl1GIZY3+86It94LAQAAAG8jIAMAoABLG5D5+fmpWbNmeeov7SijrG7cpbV06VKXwOaVV15x67zq1au77MfHx7t1Xl69+OKL5vR9/fv3180335xp27wGZEFBQeZ26o17T8jN85SQkGBuBwQEuHXOyZMnPTaSKzY2VkuXLtWWLVt0/PhxXbx4UVevXnVpk3YUz9GjRz3yuDnRrl07c1TMG2+8oQoVKmjIkCHm1H9W9ZWVmJgYPfjgg9m2O3bsmLm9dOlStwK7Bx54QA888ECe6pP+De7dmQa0cuXKatmypaKioiRJ69atc6v/RYsW6e6779aVK1ck/fv3duHChVmOAksr7ePcfPPN5np4Walbt65q1Kihw4cP56jvEiVKZNt327ZtFRwcrNOnT2fb1irpR/w+9dRT2Z6TmJjo8l6RdjSZu0JDQz0WyOcXh8Ohe++912Uk4eOPP64BAwZkeV5SUpLLvjuvy4zape/H231nxFvvhQAA5JfUKZntyK7XDaQiIAMAoADbuHGjud24cWO3g4/MpN5gltz/RHnqWj/Sv1NouTOKQJK5Jk8qTwcHGdm4caOmTZsm6d+Q6L333suyfdp1yA4dOqTz58+7PRWVJJeb4Wl/tnmVm+cpKCjIvDF54cIFj9WSnUOHDunZZ5/Vr7/+KofD4fZ5VqxBNnr0aE2fPl1Xr17V1atX9cgjj+iZZ57Rbbfdpptvvlnt27dXq1atXNbQyo++shIfH5/jEPP48eM6fvx4tu08NaIz/Xp+2bVNDch2796dbfvffvtNb7/9tvnauvnmmxUeHp6jv6eHDh0ytxs1auT2eY0bN842IEt7DTn9OURERLjdPr+lDcjq1avn1s9t586dLr8DcvKzLqxSUlI0ePBgzZ8/3zw2YMAATZo0Kdtz069HmJCQ4FbAmvbDEBn14+2+M+Kt90IAAADA21iDDACAAio5OVlbt2419/M6vWJ6TqfTrXZpb+Lecsstbn/CLO0aTZJUs2ZN94vLBafTqdGjR5vB3NixY1W7du0sz0l/Qzuno8jc/RnmhbuPUaFCBXP73Llzbp1z9913y+l0XvP12muvuXX+hg0b1KJFC/344485CsckXTO6LD80adJEc+bMUenSpc1jly5d0i+//KKxY8eqffv2CgoK0l133aUffvghy2vyZF+FXdrXXk7auvM63bhxo/mz8/Pz05QpU3IUjkmuYWxOznWnbdpryO3PoSBKG5BlNQo3rbQf6Khdu7bLqKKiKCUlRUOHDtWsWbPMY/3799fMmTPl6+ub7fnp13CMi4tz63HTt0v7Oyg/+s5IfrwXAgAAAN5AQAYAQAG1c+dOl2kJW7dunec+034a3J0pDxMTE7Vjxw5z//rrr3f7sbZt22ZuG4aR5+khszNjxgxzfStJmjx5soKDg7P86tOnj0sfOQ3I0v4M3f2kvTty+jxJcgkDjx075nZIlltXrlxRv379zPDB399fDzzwgGbNmqVt27bp7NmzSkhIyFXw5k29evXS3r179cILL1wzDaj073X99ttvuu+++9SoUSOtWbMmX/rKTK1atTIMMdN/ff311+Y5Dz74oFvnvP766zmuJyPFihVzu23aUbDuhKRdu3Y1R6c4HA5169bNZapOqyUmJprbuf05FERpAzJ333vSTgns6Q90FDQpKSl6+OGH9d1335nH+vbtq1mzZrk9nWFISIjL/okTJ9w6L3274ODgfO07I956LwQAAAC8jSkWAQAooNLebJQ8c8OxYsWK5vbZs2ezbX/o0CGXqRKvu+46tx9r+fLl5nazZs3cvtGWG5cvX9b48eNdjuVmmsGcBmRpf4Zpf7Z5ldPnSZI6deqkBQsWmPvr1q1zax2q3Pr666/NdcT8/f21dOlSderUKctzLl265LV6kpOT3W5bsWJFvfPOO3rnnXe0e/durV69WqtXr9by5ctd1lDau3evbr31Vq1evVotW7b0el+FVU6e14sXL5rbZcuWzbZ9x44d9eqrr+rOO+/U5cuXdeTIEXXq1EnLli1TgwYN3HrMcuXKKSYmRlLOpvZ0p22ZMmXMv6O5/TkUNMeOHXNZB9HdgCztCLLcvl+5u+Zebnhqzb2UlBQNHz5c33zzjXmsT58+mj17ttvhmCQ1bNjQZf/QoUNuTdOZdspQKeOpLL3Zd0a89V4IAAAAeBsBGQAABVTagMzHx0ctWrTIc59pRxmlhhtZOXnypMu+u9MtXb16VXPnzjX3e/bs6V6BuTRhwgS3PyGflZwGZGl/hrVq1crz46fK6fMk/TvSJq0ffvjBqwHZokWLzO1BgwZlG45J1067mZm0I3GSkpLcOie3I+bq16+v+vXr66GHHpIkbdmyRR9++KG+/fZbSf9OOfb888+7tQ6YJ/sqTNIGgdnZv3+/uR0aGurWOZ06ddKiRYvUs2dPXbx4UcePH1fnzp31xx9/qEmTJtmeX7NmTTMg27lzp9u1RkdHZ9smNDTUDAdy+3MoaNKOHvP393dr9K+npgTOzZp77vLEmnup4VjaEZt9+vTRnDlzcrzeYPrX7qZNm3TnnXdme176D880btw4X/vOiLfeCwEAyC+GYbi9lEBRY9frBlIxxSIAAAVU2htVDRo0MKcZy4umTZua2+5MU5b+0/DurmMyc+ZM86axj4+PRo4cmYMqc2bv3r36+OOPzf3ffvvNrenlUr9eeukl89zo6GiXKdPceexU7nw63105fZ4kqU2bNi43pefMmXNNwOlJaUcatG3bNtv2TqfTZQrMrJQpU8bcdncEXdopPfOiefPmmj59uu6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      "text/plain": [
       "<Figure size 1000x1600 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1479,
       "width": 868
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %load ./code/fig_likelihood_gausslin.py\n",
    "# Author: Jake VanderPlas\n",
    "# License: BSD\n",
    "#   The figure produced by this code is published in the textbook\n",
    "#   \"Statistics, Data Mining, and Machine Learning in Astronomy\" (2013)\n",
    "#   For more information, see http://astroML.github.com\n",
    "#   To report a bug or issue, use the following forum:\n",
    "#    https://groups.google.com/forum/#!forum/astroml-general\n",
    "from scipy.stats import truncnorm, uniform\n",
    "from astroML.plotting.mcmc import convert_to_stdev\n",
    "\n",
    "def gausslin_logL(xi, A=0.5, sigma=1.0, mu=5.0, L=10.0):\n",
    "    \"\"\"Equation 5.80: gaussian likelihood with uniform background\"\"\"\n",
    "    xi = np.asarray(xi)\n",
    "\n",
    "    shape = np.broadcast(sigma, A, mu, L).shape\n",
    "\n",
    "    xi = xi.reshape(xi.shape + tuple([1 for s in shape]))\n",
    "\n",
    "    return np.sum(np.log(A * np.exp(-0.5 * ((xi - mu) / sigma) ** 2)\n",
    "                         / (sigma * np.sqrt(2 * np.pi))\n",
    "                         + (1. - A) / L), 0)\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# Define the distribution\n",
    "np.random.seed(0)\n",
    "mu = 5.0\n",
    "sigma = 1.0\n",
    "L = 10.0\n",
    "A = 0.5\n",
    "N = 200\n",
    "\n",
    "xi = np.random.random(N)\n",
    "NA = np.sum(xi < A)\n",
    "\n",
    "dist1 = truncnorm((0 - mu) / sigma, (L - mu) / sigma, mu, sigma)\n",
    "dist2 = uniform(0, 10)\n",
    "\n",
    "xi[:NA] = dist1.rvs(NA)\n",
    "xi[NA:] = dist2.rvs(N - NA)\n",
    "\n",
    "x = np.linspace(-1, 11, 1000)\n",
    "fracA = NA * 1. / N\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# define the (sigma, A) grid and compute logL\n",
    "sigma = np.linspace(0.5, 2, 70)\n",
    "A = np.linspace(0, 1, 70)\n",
    "\n",
    "logL = gausslin_logL(xi, A[:, np.newaxis], sigma)\n",
    "logL -= logL.max()\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# Plot the results\n",
    "fig = plt.figure(figsize=(10, 16))\n",
    "fig.subplots_adjust(bottom=0.07, left=0.11, hspace=0.15, top=0.95)\n",
    "\n",
    "ax = fig.add_subplot(211)\n",
    "plt.imshow(logL, origin='lower', aspect='auto',\n",
    "           extent=(sigma[0], sigma[-1], A[0], A[-1]),\n",
    "           cmap=plt.cm.binary)\n",
    "plt.colorbar().set_label(r'$\\log(L)$')\n",
    "plt.clim(-5, 0)\n",
    "ax.set_xlabel(r'$\\sigma$')\n",
    "ax.set_ylabel(r'$A$')\n",
    "\n",
    "ax.text(0.5, 0.9, r'$L(\\sigma,A)\\ (\\mathrm{Gauss + bkgd},\\ n=200)$',\n",
    "        bbox=dict(ec='k', fc='w', alpha=0.9),\n",
    "        ha='center', va='center', transform=plt.gca().transAxes)\n",
    "\n",
    "ax.contour(sigma, A, convert_to_stdev(logL),\n",
    "           levels=(0.683, 0.955, 0.997),\n",
    "           colors='k')\n",
    "\n",
    "ax2 = plt.subplot(212)\n",
    "ax2.yaxis.set_major_locator(plt.MultipleLocator(0.1))\n",
    "ax2.plot(x, fracA * dist1.pdf(x) + (1. - fracA) * dist2.pdf(x), '-k')\n",
    "ax2.hist(xi, 30, density=True, histtype='stepfilled', fc='gray', alpha=0.5)\n",
    "\n",
    "ax2.set_ylim(0, 0.301)\n",
    "ax2.set_xlim(-1, 11)\n",
    "\n",
    "ax2.set_xlabel('$x$')\n",
    "ax2.set_ylabel('$p(x)$')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "A more realistic example might be one where all three parameters are unknown: the location, the width, and the background level. *But that will have to wait until we learn about MCMC numerical techniques.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Bayesian Model Comparison <a class=\"anchor\" id=\"two\"></a>\n",
    "\n",
    "Model comparison and hypothesis testing in Bayesian inference are enormously different from classical/frequentist statistics. We don't have p-values here. ***In Bayesian inference, we probabilistically rank models based on how well they explain the data under our prior knowledge.*** Let's look back at how we assessed goodness-of-fit and model choice in frequentist statistics. \n",
    "\n",
    "Let's use the example from http://jakevdp.github.io/blog/2015/08/07/frequentism-and-bayesianism-5-model-selection/\n",
    "to illustrate some ideas about model selection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "#Execute this cell to load all of the modules we'll need and define the data array.\n",
    "from scipy import stats\n",
    "from scipy import optimize\n",
    "\n",
    "# generate (x,y, sigma_y) \"data\" \n",
    "data = np.array([[ 0.42,  0.72,  0.  ,  0.3 ,  0.15,\n",
    "                   0.09,  0.19,  0.35,  0.4 ,  0.54,\n",
    "                   0.42,  0.69,  0.2 ,  0.88,  0.03,\n",
    "                   0.67,  0.42,  0.56,  0.14,  0.2  ],\n",
    "                 [ 0.33,  0.41, -0.25,  0.01, -0.05,\n",
    "                  -0.05, -0.12,  0.26,  0.29,  0.39, \n",
    "                   0.31,  0.42, -0.01,  0.58, -0.2 ,\n",
    "                   0.52,  0.15,  0.32, -0.13, -0.09 ],\n",
    "                 [ 0.1 ,  0.1 ,  0.1 ,  0.1 ,  0.1 ,\n",
    "                   0.1 ,  0.1 ,  0.1 ,  0.1 ,  0.1 ,\n",
    "                   0.1 ,  0.1 ,  0.1 ,  0.1 ,  0.1 ,\n",
    "                   0.1 ,  0.1 ,  0.1 ,  0.1 ,  0.1  ]])\n",
    "\n",
    "x,y, sigma_y = data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 426,
       "width": 688
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.errorbar(x, y, sigma_y, fmt='ok', ecolor='gray');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Is this data linear or quadratic?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "#Functions to do a polynomial fit, compute the likelihood, and determine the best-fit parameters.\n",
    "\n",
    "def polynomial_fit(theta, x):\n",
    "    \"\"\"Polynomial model of degree (len(theta) - 1)\"\"\"\n",
    "    # For a polynomial with order 1, this gives theta_0 + theta_1*x\n",
    "    # For a polynomial with order 2, this gives theta_0 + theta_1*x + theta_2*x^2, etc.\n",
    "    return sum(t * x ** n for (n, t) in enumerate(theta))\n",
    "\n",
    "# compute the data log-likelihood given a model\n",
    "def logL(theta, data, model=polynomial_fit):\n",
    "    \"\"\"Gaussian log-likelihood of the model at theta\"\"\"\n",
    "    x, y, sigma_y = data\n",
    "    y_fit = model(theta, x)\n",
    "    return sum(stats.norm.logpdf(*args) for args in zip(y, y_fit, sigma_y))\n",
    "\n",
    "# a direct optimization approach is used to get best model \n",
    "# parameters (which minimize -logL)\n",
    "def best_theta(degree, model=polynomial_fit, data=data):\n",
    "    theta_0 = (degree + 1) * [0]\n",
    "    neg_logL = lambda theta: -logL(theta, data, model)\n",
    "    return optimize.fmin_bfgs(neg_logL, theta_0, disp=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 471,
       "width": 711
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Execute this cell.  See if you understand what it is doing.\n",
    "x, y, sigma_y = data\n",
    "Ndata = x.size\n",
    "\n",
    "# get best-fit parameters for linear, quadratic and cubic models\n",
    "theta1 = best_theta(1, data=data)\n",
    "theta2 = best_theta(2, data=data)\n",
    "theta3 = best_theta(3, data=data)\n",
    "# generate best fit lines on a fine grid \n",
    "xgrid = np.linspace(-0.1, 1.1, 1000)\n",
    "yfit1 = polynomial_fit(theta1, xgrid)\n",
    "yfit2 = polynomial_fit(theta2, xgrid)\n",
    "yfit3 = polynomial_fit(theta3, xgrid)\n",
    "\n",
    "# plot \n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.errorbar(x, y, sigma_y, fmt='ok', ecolor='gray')\n",
    "ax.plot(xgrid, yfit1, label='best linear model')\n",
    "ax.plot(xgrid, yfit2, label='best quadratic model')\n",
    "ax.plot(xgrid, yfit3, label='best cubic model')\n",
    "ax.legend(loc='best', fontsize=14)\n",
    "ax.set(xlabel='x', ylabel='y', title='data');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "We can use $\\chi^2$ per degree of freedom to determine which fit is \"best\".  It is computed as \n",
    "\n",
    "$$ \\chi^2_\\mathrm{dof}  = \\frac{1}{N-k} \\sum_i^N \\left( \\frac{y - y_\\mathrm{fit}}{\\sigma_y} \\right)^2, $$\n",
    "\n",
    "where $N$ is the number of data points and $k$ is the number of free model parameters (here 2, 3, and 4).\n",
    "\n",
    "For large values of $(N-k)$ (larger than about 10), the distribution of \n",
    "$\\chi^2$ per degre of freedom is approximately Gaussian with a width of\n",
    "$\\sigma=\\sqrt{2/(N-k)}$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CHI2:\n",
      "   best linear model: 11.499462014956965\n",
      "   best quadratic model: 9.291258246116401\n",
      "   best cubic model: 8.979208294682907\n",
      "CHI2 per degree of freedom:\n",
      "   best linear model: 0.6388590008309425\n",
      "   best quadratic model: 0.5465446027127294\n",
      "   best cubic model: 0.5612005184176817\n"
     ]
    }
   ],
   "source": [
    "#Compute chi2: sum{[(y-yfit)/sigma_y]^2} \n",
    "chi21 = np.sum(((y-polynomial_fit(theta1, x))/sigma_y)**2) \n",
    "chi22 = np.sum(((y-polynomial_fit(theta2, x))/sigma_y)**2) \n",
    "chi23 = np.sum(((y-polynomial_fit(theta3, x))/sigma_y)**2) \n",
    "# normalize by the number of degrees of freedom\n",
    "# the number of fitted parameters is 2, 3, 4\n",
    "chi2dof1 = chi21/(Ndata - 2)\n",
    "chi2dof2 = chi22/(Ndata - 3)\n",
    "chi2dof3 = chi23/(Ndata - 4)\n",
    "\n",
    "print(\"CHI2:\")\n",
    "print('   best linear model:', chi21)\n",
    "print('   best quadratic model:', chi22)\n",
    "print('   best cubic model:', chi23)\n",
    "print(\"CHI2 per degree of freedom:\")\n",
    "print('   best linear model:', chi2dof1)\n",
    "print('   best quadratic model:', chi2dof2)\n",
    "print('   best cubic model:', chi2dof3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "**Which model should we adopt?**\n",
    "\n",
    "Obviously, the cubic model has the lowest $\\chi2$ (\"fits the best\"), but \n",
    "it has 4 free parameters while the linear model has only 2 free parameters.\n",
    "\n",
    "**How do we trade improvement in $\\chi^2$ with increasing model complexity?**\n",
    "\n",
    "**Occam’s razor:**\n",
    "> *All else being equal (i.e., each model fits the data equally well), the less complex model is favored.*\n",
    "\n",
    "This principle was already known to [Ptolemy](https://www.wikiwand.com/en/Ptolemy) (circa 100-170 AD) who said: *“We consider it a good principle to explain the phenomena by the simplest hypothesis possible.”*"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
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   "source": [
    "## Bayesian Model Comparison\n",
    "\n",
    "We start with Bayes' Theorem,\n",
    "\n",
    "$$ \\mathrm{Posterior} = \\frac{\\mathrm{Likelihood}\\times\\mathrm{Prior}}{\\mathrm{Evidence}} $$\n",
    "\n",
    "$$p(M,\\theta \\,|\\,D,I) = \\frac{p(D\\,|\\,M,\\theta,I)\\,\\times p(M,\\theta\\,|\\,I)}{p(D\\,|\\,I)},$$\n",
    "\n",
    "and marginalize over model parameter space $\\theta$\n",
    "to obtain **the probability of model $M$** given the data $D$ and prior information $I$:\n",
    "\n",
    "$$p(M\\,|\\,D,I) \\equiv \\int p(M,\\theta \\,|\\,D,I) \\, d\\theta = \n",
    "      \\int \\frac{p(D\\,|\\,M,\\theta,I)\\,p(M,\\theta\\,|\\,I)}{p(D\\,|\\,I)} \\, d\\theta =\n",
    "      \\frac{p(M\\,|\\,I)}{p(D\\,|\\,I)} \\int p(D\\,|\\,M,\\theta,I)\\,p(\\theta\\,|\\,M,I) \\, d\\theta  $$\n",
    " \n",
    " \n",
    "#### Odds Ratios \\& Bayes Factors\n",
    "\n",
    "To determine which model is better we compute the ratio of the posterior probabilities or the **odds ratio** for two models as\n",
    "\n",
    "$$O_{21} \\equiv \\frac{p(M_2|D,I)}{p(M_1|D,I)}.$$\n",
    "\n",
    "The meaning of this number is like *\"If $O_{21}=10$ and I bet 10 Euros against 1 Euro in favour of model 2 against model 1, then the bet is fair\"* (of course considering the info $I$ at my disposal).\n",
    "\n",
    "\n",
    "The posterior probability that the model $M$ is correct given data $D$ (a number between 0 and 1) is\n",
    "\n",
    "$$p(M|D,I) = \\frac{p(D|M,I)p(M|I)}{p(D|I)},$$\n",
    "\n",
    "the odds ratio can ignore $p(D|I)$ since it  will be the same for both models.  \n",
    "\n",
    "We get \n",
    "\n",
    "$$O_{21} = \\frac{p(D\\,|\\,M_2,I)\\,p(M_2\\,|\\,I)}{p(D\\,|\\,M_1,I)\\,p(M_1\\,|\\,I)} \\equiv B_{21} \\, \\frac{p(M_2\\,|\\,I)}{p(M_1\\,|\\,I)},$$\n",
    "\n",
    "where $B_{21}$ is called the **Bayes factor**. \n",
    "\n",
    "- The Bayes factor compares how well the models fit the data. \n",
    "- It is a ratio of data likelihoods averaged over all allowed values of the model parameters. \n",
    "- If two models fit the data equally well, the \"winner\" is decided based on priors. \n",
    "\n",
    "And this makes perfect sense! Consider a noisy image of a source which is equally likely to be a star or a galaxy. \n",
    "The posterior probability that the source is a star will greatly depend on whether we are looking \n",
    "at the Galactic plane or not. \n",
    "\n",
    "![](https://cdn.mos.cms.futurecdn.net/F2hDqo3nTCxLrbo68HPEUE-970-80.jpg.webp)\n",
    "\n",
    "\n",
    "#### Bayesian Evidence \n",
    "\n",
    "We can compute \n",
    "\n",
    "$$ E(M) \\equiv p(D\\,|\\,M, I) = \\int p(D\\,|\\,M, \\theta, I) \\, p(\\theta\\,|\\,M, I) \\, d\\theta, $$\n",
    "\n",
    "where $E(M)$ is called **the marginal likelihood for model $M$ (or \"evidence\" or \"fully marginalized likelihood\")** and it quantifies the probability that the  data $D$ would be observed if the model $M$ were the correct model. *Note: the symbol for Bayesian evidence is sometimes $\\mathcal{Z}$; check for context!*\n",
    "\n",
    "The evidence is a weighted average of the likelihood function with the prior for model parameters acting as the weighting function. \n",
    "\n",
    "In standard parameter estimation, that's the thing at the denominator in Bayes' theorem. Say you want to measure a parameter $\\theta$ from a model $M$ (like we did with the fit above) one can write\n",
    "\n",
    "$$p(\\theta | D, M) = \\frac{p(D | \\theta, M) p(\\theta | M)}{p(D|M)}$$\n",
    "\n",
    "so that's precisely the term that we ignored so far.\n",
    "\n",
    "\n",
    "#### How do we interpret the values of the odds ratio in practice?\n",
    "\n",
    "**Jeffreys** proposed a scale for interpreting the odds ratio, where $O_{21} > 10$ represents *“strong”* evidence in favor of $M_2$ ($M_2$  is ten times more probable than $M_1$), and $O_{21} > 100$ is *“decisive”* evidence ($M_2$ is one hundred  times more probable than $M_1$). When $O_{21} < 3$, the evidence is *“not worth more than a bare mention.”*\n",
    "\n",
    "The table below uses Bayes factors, which are numerically equivalent to odds ratios whenever we ascribe equal priors odds to our models.\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "But note:\n",
    "  * These are just **definitions of conventions**, i.e., a way to give a quantitative meaning to qualitative phrases.\n",
    "  * The odds ratio **compares** the models, it doesn't tell us about the *absolute* goodness of fit: model A can be 100x better than model B, but still be pretty lousy.\n",
    "  * Remember: \"***GIGO***\" ***= Garbage In, Garbage Out***. If we use our powerful statistics to rank a bunch of lousy models, that's our fault."
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Hypothesis Testing\n",
    "\n",
    "In *hypothesis testing* we are essentially comparing a model, $M_1$, to its complement.  That is $p(M_1) + p(M_2) = 1$.  If we take $M_1$ to be the \"null\" (default) hypothesis (which is generally that, for example, a correlation does *not* exist), then we are asking whether or not the data reject the null hypothesis.\n",
    "\n",
    "- In **classical hypothesis testing** we can ask whether or not a single model provides a good description of the data.  \n",
    "- In **Bayesian hypothesis testing**, we need to have an alternative model to compare to.\n",
    "\n",
    "\n",
    "Here is another example of a recent paper from my research field: *Who Ordered That? Unequal-mass Binary Black Hole Mergers Have Larger Effective Spins* by Callister et al [arxiv:2106.00521](https://arxiv.org/abs/2106.00521). Using an exquisitely Bayesian approach, they look for correlations between the masses and the spins of the binary black holes detected by LIGO. Good stats in there!\n",
    "\n",
    "\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example of Cauchy Versus Gaussian Model Comparison <a class=\"anchor\" id=\"twoa\"></a>\n",
    "\n",
    "We now draw a sample from a Cauchy distribution (remember, it has heavy tails!) and perform Bayesian Model Comparison for Cauchy and Gaussian models. The Bayesian evidence is computed as a direct brute-force numerical integral over parameter space-- no stochasting sampling methods are used here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results for first 10 points:\n",
      "  L(M = Cauchy) = 1.18e-12 +/- 5.39e-16\n",
      "  L(M = Gauss)  = 8.09e-13 +/- 7.45e-16\n",
      "Bayesian odds ratio of Cauchy-versus-Gaussian Models = 1.45 +/- 0.00134\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/dgerosa/box/lib/python3.11/site-packages/scipy/integrate/_quadpack_py.py:1225: IntegrationWarning: The algorithm does not converge.  Roundoff error is detected\n",
      "  in the extrapolation table.  It is assumed that the requested tolerance\n",
      "  cannot be achieved, and that the returned result (if full_output = 1) is \n",
      "  the best which can be obtained.\n",
      "  quad_r = quad(f, low, high, args=args, full_output=self.full_output,\n",
      "/Users/dgerosa/box/lib/python3.11/site-packages/scipy/integrate/_quadpack_py.py:1225: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
      "  quad_r = quad(f, low, high, args=args, full_output=self.full_output,\n",
      "/Users/dgerosa/box/lib/python3.11/site-packages/scipy/integrate/_quadpack_py.py:1225: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.\n",
      "  If increasing the limit yields no improvement it is advised to analyze \n",
      "  the integrand in order to determine the difficulties.  If the position of a \n",
      "  local difficulty can be determined (singularity, discontinuity) one will \n",
      "  probably gain from splitting up the interval and calling the integrator \n",
      "  on the subranges.  Perhaps a special-purpose integrator should be used.\n",
      "  quad_r = quad(f, low, high, args=args, full_output=self.full_output,\n"
     ]
    },
    {
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NXq9Xs2fP1htvvBFy/KqrrtL999+vxMTE6BYGAN0cK28BAAAAAEBIx662DRXcjhgxQn/729/0hz/8geAWACKAlbcAAAAAAKAFr9era665Rm+++WbI8by8PN1zzz0aMGBAlCsDgJ6DlbcAAAAAACCgqalJjzzyiMaPHx8yuD3jjDNUXl6uJUuWENwCQISx8hYAAAAAAEhqf7Xt3LlzVVRURGgLAFFCeAsAAAAAQA/X1NSkxx57TC6XS3v37m0xfsYZZ+jJJ5/UtGnTTKgOAHouwtsI8Hg8crlcstvt8nq9MgxDBQUFcjgcQfO8Xq9cLpeSkpIkSQ0NDSHnAQAAAAAQKdXV1Zo9ezarbQHAgghvw8zj8WjRokUqLy8PHHO5XEpLS1NVVVUgmPX5fEpLS1NFRUXgmNfrDcwzDMOU+gEAAAAAPUNTU5MeffRRLViwgNW2AGBRbFgWZosWLWoRvBYWFsput8vlcrWYd+wqW8MwlJGRocLCwqjVCwAAAADoeaqrqzV16lRdd911IYPbuXPnauPGjQS3AGAywtswS0pKksfjaXHcMAx5vd7Aa7fbrcmTJ4ec53a7I1ojAAAAAKBnampq0sMPP6wJEyaEbJNwxhlnyO126/HHH6dNAgBYQI8Pb10ul1JTU9ud53a7lZmZqby8PDmdTjmdzqAwtllxcXFQywTpaIsEj8ejjIyMwLFQAa8kDRo0KOR1AQAAAAA4EdXV1brkkktaXW07b948VtsCgMX0yJ63TqdTPp9PhmFo+fLl7c4vKipScXGxqqqqZLfbJR0Nc4/vWdua5s3LOtMOwefzBe4FAAAAAEBXdaS37VNPPaWpU6eaUB0AoC09MrwtLS0NPK+srGxzpavX65XL5VJpaWlQmJqRkaGMjAw5nU5VV1e3en5RUZEqKytVU1PTqTCW4BYAAAAAcKKqq6t1zTXXaPXq1SHH582bp8LCQlokAIBF9cjwtjPKysokKajlQbOcnByVlZXJ4/GEXH3rcrnk8/lUVVXVYszhcKihoaHF8R07dhDcAgAAAEA31NjYqKVLlwZ6zSYkJMhut7f5tfl53759ZbPZOnyv9lbbjhw5Uk8++SSrbQHA4ghv27Fs2TJJoVfCNh9btmxZi/A2Ly9PmZmZys7ODhxzOp2BVb8ZGRkhNyY7vjduZ9TX17c7Z/jw4V26NgAAAACY5aOPPtLKlSv1t7/9TSeddJL+4z/+Q7NmzVKfPn3MLq1Dtm/frgcffFAPP/ywGhsbu3SN3r17txv0Nn/t37+/HnrooVZX2/76179WYWGh+vfvfyJvCwBiRl1dXZvjHcnUzGLz+/1+s4swU1pamrxer3bu3Bly3GazyW63hxz3er1KTU1VRkZG0CZlmZmZstvtSk9PDxzbsWOHvF5vILz1+XwaNWpUUM9cr9ertLQ0VVVVyTCMDtVfV1enlJSUDr/fHv6fGwAAAEAM8Pv9WrdunVauXKkVK1Zo06ZNLeYMHTpU//mf/6m5c+fq1FNPNaHK9n311Ve67777VFxcHHL1a7Sx2hZAT9WZ31yora211OJHVt62wefzdWjese0PnE5nYEVtc8uFZsduWGa321VVVSWXy6WkpKTAdSoqKjoc3AIAAABAd9HU1KT33ntPK1as0MqVK1VTU9Pm/C1btujmm2/WXXfdpSuvvFLXX3+9zjrrrChV2zav16vCwkI9/fTTOnjwoNnlSGK1LQDEKsLbMDt2M7T2GIbRqfntWbNmjZKTk8N2PQAAAACIpMOHD+sf//iHVqxYoZdeeklff/11p6+xf/9+lZSUqKSkRJdeeql++9vfKiMjo1OrrMLlww8/1OLFi/XCCy/oyJEjrc6bMWOG0tLS1NjYKJ/P1+rXffv2nXBNI0eO1FNPPaVLLrnkhK8FALGqtra2zfH6+npNmTIlStV0DuFtG2Jt47Dk5GRLLesGAAAAgOMdPHhQFRUVWrFihf7yl79o+/btHTrv9NNP189+9jN99NFH+vvf/x5yzt/+9jf97W9/07nnnqvrr79ev/jFL9S3b99wlh9SZWWl7r77br300kutzomPj9cVV1yhBQsW6Oyzz+7QdQ8ePKjGxsZ2Q95QX/v27auf/vSnuummm1htC6DHi+W8jPD2BDS3VWhuewAAAAAAaGnv3r167bXXtHLlSv31r3/t8KZdhmEoKytLWVlZSk9PV1xcnCRp3bp1euCBB/TCCy/o0KFDLc774IMPdO2116qgoEC//vWvNW/ePA0ZMiSs70mSVq9erbvuukurVq1qdc5JJ52ka665Rvn5+Ro1alSnrn/SSSdp8ODBGjx48ImWCgCIUXFmF2B1hmG02vu2uddt84ZjAAAAAICjdu3apRdffFFOp1ODBw/WjBkz9Kc//and4Pbss8/WzTffrHXr1unzzz9XUVGRvvOd7wSCW0maNGmS/vjHP+qLL77QTTfdpEGDBoW81rZt23T77bdrxIgRmj17tjZu3HjC78vv9+vVV1/V9773PV188cWtBrf9+vXT/PnzVVNTo8cff7zTwS0AABLhbbsyMjIkhd68zOv1SpJycnKiWRIAAAAAWFJDQ4Oefvpp/eQnP9HgwYN1+eWXq6ysTHv37m3zPIfDoTvvvFMff/yxPvzwQ91xxx2aOHFiu31rk5OTdeedd+rLL7/UkiVLNG7cuJDzDh48qKeeekoTJkxQZmamXn31VTU1NXXqvTU1NamsrExpaWn60Y9+pLfeeivkPLvdrltuuUVffPGF7r33Xg0bNqxT9wEA4Fg2v9/vN7sIM6Wlpcnr9Wrnzp0hx71er1JTU1VcXKzc3NygMafTKbfb3eq50VBXV6eUlBRJR5svx3IPDwAAAACx5ZtvvtF7772nd999V2+//bbeeuutNjfqOtYFF1ygrKwszZgxI2yrUpuamvTaa6/p/vvvl9vtbnPuuHHjdP311+tXv/qVTjnllFbnHTp0SM8//7wWL16sTZs2tTrvtNNO029/+1vNmzdPAwcO7PJ7AABEn5XztR4f3qampsrr9aqt/xlcLpdKSkpUU1MT2MTM7XYrMzNTVVVVprZNsPI3FwAAAIDu49ChQ9qwYYPeffddvfPOO3r33XcDv43YEXFxcbr44ouVlZWln/3sZzr99NMjWK20ceNGPfDAA/rTn/6kgwcPtjpv0KBBmjt3rv7zP/9TycnJgeP79+/XH/7wBxUVFWnz5s2tnp+SkqL8/HzNnj1bJ598cjjfAgAgSqycr1kyvH3iiSdUXl4uwzA0ffp0XXLJJWG9vsvlksfjUUNDgzwej6SjvW2bH8XFxS3OKSsrU3FxcSC8laTCwkIZhhHW2jrLyt9cAAAAAGLXV199pXfffTcQ1lZVVWn//v2dukbv3r01bdo0ZWVl6ac//akpG29t3bpVjz/+uB577DFt27at1Xm9e/fWrFmzNG/ePL399tu67777tGXLllbnjxkzRgUFBfrFL36hk046KRKlAwCixMr5minh7fTp01VVVSVJSkpKksvl0rXXXitJSk9Pl8fjkd/vl2EY8nq9mjt3rh577LFolxkTrPzNBQAAACA27N+/Xx6PJ2hVbV1dXZeu1bdvX1166aXKysrSZZddFrQAxkz79+/Xc889p9///vf68MMPu3yd8847TwsXLlRWVpbi4+PDWCEAwCxWztd6mXHTxYsXKyMjQ0uXLlVWVlbgeEFBgaqqqpSamqpVq1YF+h5Nnz5dr7/+uqZOnWpGuQAAAADQbfj9fm3evDloVe369et16NChLl2vX79+Sk9P1wUXXKDzzz9fU6dOVf/+/cNc9Ynr27evZs+erWuuuUbl5eX6/e9/r7/97W8dPv/888/XTTfdpB//+MftbqQGAEC4mLLy9t5779W0adM0adKkwLHGxkYlJibKZrOpqqpKEydODIz5fD7l5eVp2bJl0S7V8qz8kwEAAAAA1vDRRx/p5ZdfDgS2W7du7fK1xo4dq/PPPz8Q1p5zzjnq1cuUdUEn7KOPPtIDDzygZ599ttWWEBkZGVq4cKG+//3vE9oCQDdl5XzNlP+Hra6u1g033BB0rHknUMMwgoJbSbLb7W1uKAYAAAAAaGnfvn1auHChHnzwwS79myohIUHf+c53AmHtlClTlJSUFIFKzXH22WerpKREd911l4qLi/XII48Egu1///d/18KFC/Wd73zH5CoBAD2ZZX48unbtWkmSw+EIOc5POAEAAACg49asWaMrr7xSn3zySYfm22w2nXvuuTr//PMDYe3YsWMVFxcX4UrNN3jwYP2///f/dOONN8rj8WjYsGE644wzzC4LAABzwtuGhoYWxzwej2w2mzIzM0Oe4/P5IlwVAAAAAMS+gwcP6o477tCiRYvU1NTU6rxTTz01ENSef/75Sk9P18CBA6NYqfX06dNHF1xwgdllAAAQYEp4G+rXddxut2w2myZPntxirKamJrB5GQAAAAAgtA0bNujKK6/U+++/32KsT58+uvrqq3XRRRfp/PPPV2pqKr/hCACAxZkS3qanp2vlypWaMWOGJKmgoEBS6H63u3bt0ty5c1VcXBztMgEAAAAgJhw+fFiFhYW6/fbbdejQoRbj6enp+uMf/6izzjrLhOoAAEBXmRLe3njjjRo9erSWLVsmr9erqqoq2Wy2oIB2165dWr58uVwul5KSkjRo0CAzSgUAAAAAS9u0aZOuvPLKwD4ix+rdu7duvfVWuVwu9eplmS1PAABAB5nWeb6qqkp2u107d+6Uw+HQqlWrNHXqVEnSihUrNHLkSOXn58vv92vHjh2BMQAAAACA1NTUpN///veaNGlSyOB2woQJWrNmjW666SaCWwAAYpTNH6oBLWJGXV2dUlJSJEm1tbUaPny4yRUBAAAAiDSv16urr75aq1evbjEWFxenBQsW6JZbblGfPn1MqA4AgNhi5XyNH78CAAAAQIzw+/0qKSnR/PnztWfPnhbjZ555pp555hl95zvfMaE6AAAQbqa1TQAAAAAAdFxdXZ0uvfRSzZ07N2Rwe/3112vdunUEtwAAdCOmrLxdv369Jk6c2Or49OnTZbPZJEkOh0MFBQUaOHBglKoDAAAAAOvw+/169tlndd1116mxsbHF+MiRI/WHP/xB3//+96NfHAAAiChTwtu0tDQdOXKk1fFVq1YFnq9bt07Z2dkqKipqM/AFAAAAgO5m69atysvL01/+8peQ47m5ubr33ns1YMCAKFcGAACiwZS2CZ3ZI23SpElatWqVFi1aFMGKAAAAAMBaysrKdM4554QMbocNG6ZXX31VxcXFBLcAAHRjpoS3zS0ROsPr9UagEgAAAACwloaGBl1xxRVyOp3asWNHi/Ff/vKX+uCDD3TppZeaUB0AAIgmU9omdNaKFSvk8/nMLgMAAAAAIup///d/NWfOHNXX17cYGzx4sJYsWaIZM2aYUBkAADBDRMPbuXPntrrKdt68eR26htvtltfrVWFhYThLAwAAAADL2LVrl37729/qySefDDk+Y8YMPf744zrttNOiXBkAADBTRMPbvLw8eb1erV27VmVlZfJ6vbLZbPL7/SouLu7wdTIyMnTDDTdEsFIAAAAAMMfrr7+uq6++Wl9++WWLMbvdrkceeURXXHFFl9rPAQCA2Gbzd2b3sBNUUlISWI07Z86cduenpqbK4XBo2rRpUaguNtXV1SklJUWSVFtbq+HDh5tcEQAAAICO2L59u2688UY9/fTTIcd/+MMfaunSpTr99NOjWxgAAD2MlfO1qPa8zc3NVVJSknJycrRkyZJo3hoAAAAALMHv9+uZZ57R/PnzQ25I1r9/f/3+97/X7NmzWW0LAEAPF/UNy7KzszVq1Kho3xYAAAAATPfJJ59o7ty5euONN0KOf//739cf/vAHjRw5Mqp1AQAAa4oz46ad6Xfb7PXXX49AJQAAAAAQeQcOHNDtt9+uCRMmhAxuBwwYoEceeUQVFRUEtwAAICDqK28ldamHbWZmpo4cORKBagAAAAAgct544w3NnTtXn3zyScjx7OxsPfDAA/S2BQAALZiy8razGhsbFcV91QAAAADghG3fvl1XX321LrnkkpDB7YgRI/TXv/5VpaWlBLcAACAkU1beNnviiSdUXl4un8+nhoaGVud5vV4a9QMAAACICe1tSBYfH6//+Z//0a233qr+/fubUCEAAIgVpoS3jY2NMgxDPp+vwytqCW8BAAAAWF17G5Klp6erpKREEydOjGpdAAAgNpkS3rpcLu3cuVO5ublKTU2V3W5vc35lZaWeeOKJ6BQHAAAAAJ104MABLV68WHfffbcOHjzYYnzAgAG6++67NW/ePMXHx5tQIQAAiEWmhLeVlZWqrq7WqFGjOjR/zpw5hLcAAAAALKm9DcmysrL04IMP0tcWAAB0mikbliUlJXU4uG3W2fkAAAAAEEkd2ZDs5ZdfVllZGcEtAADoElPC29TU1E6f8/nnn0egEgAAAADoHL/frz/+8Y8aN26cnn766Rbj8fHxmj9/vj788EP95Cc/iX6BAACg2zAlvPX7/dq1a1enznn99dcjVA0AAAAAdMwnn3yiqVOn6qqrrtKOHTtajKenp2vt2rW699571b9/fxMqBAAA3Ykp4e3ixYs1Z86cTp2TmZkZoWoAAAAAoG0HDhzQ7bffrgkTJuiNN95oMT5gwAA9/PDDeueddzRp0qToFwgAALolU8Jbu92uBQsWKCcnRxs2bGh3fmNjo/x+fxQqAwAAAIBgb7zxhs477zzddtttOnjwYIvxrKwsffzxx/qv//ovxcfHm1AhAADornqZcdN58+ZJOto+weFwSJIcDoeSkpJCzq+srJTNZotafeHg9XpVVlam4uJiVVdXtzrP5/PJ5XLJbrcHXhcXF0epSgAAAADNtm/frk2bNunjjz/Wpk2bAs9rampCzh8xYoQeeeQR+toCAICIMSW8XbZsWYvVtFVVVW2eE0vhrdPpVHp6uqqrq9XQ0NDqPI/Ho2nTpmnp0qXKzs4OnFtSUqLc3NxolQsAAAD0GEeOHNEXX3wRFM42fw3VwzaU+Ph4XX/99brtttvoawsAACLKlPC2eYVtQUFBYMVpW1atWqWVK1dGuKrwKS0tlSQVFRW1Oc/pdKqgoCAQ3EpHA136+wIAAAAnZt++ffr000+DwtlNmzbp008/1f79+7t83fT0dBUXF9PXFgAARIUp4a1hGFqwYIGuvfbaDs2fM2dOt+sdVVRUJK/Xq/z8/KDjbbVYAAAAABBs+/bt+vjjj1u0Ovjiiy/Cum9GYmKi7rjjDs2bN6/b/dsEAABYl2nhrWEYnTonISEhIrW4XC6VlZW1G5q63W4VFhbKMIxAK4Tm111RXl4uh8Mht9stj8ejHTt2yOv1Ki8vTxkZGV26JgAAANBdHTlyRJ9//rnWr1+vDRs2BL5+/fXXYb1P7969deaZZ2rcuHE666yzNG7cOI0bN07nnnuu+vTpE9Z7AQAAtMeU8HbJkiWdPqet3rGd5XQ65fP5ZBiGli9f3u78oqIiFRcXq6qqKtDmwe12Ky0tTRUVFYFN1zqjsrJS0tENyppX3/p8PiUmJqq0tDSolQIAAADQk+zevVvvv/++NmzYEAhqN27cqH379oXtHna7PSicbX4+atQo9eplyj+TAAAAWuiRfytp7kkrHQ1RvV5vq3O9Xq9cLpdKS0uD+vNmZGQoIyNDTqezS60Omvv+HhvS2u12ZWdna86cOYS3AAAA6Pb8fr9qa2sDq2ibg9pwthIbMWJEyJD2tNNOi6lNkQEAQM8UM+FtfHy8jhw5EvX7lpWVSVLIVgY5OTkqKyuTx+Pp9OrbY9svHCspKUk+n69LtQIAAABWdeDAAX300Uct2h6E4+++J510UshWB2PHjlW/fv1OvHgAAACTxER429jYGNbNBjpj2bJlkhS06rZZ87Fly5Z1OrzNzMzUokWLWhxvaGjoUhsGAAAAwCqOHDmiDRs2aPXq1aqqqtL69eu1adMmHT58+ISvPXToUJ133nmaOHGizjvvPJ133nk688wzaXUAAAC6pYj8DWf9+vVatGiRpk+frtmzZ7cYz8nJ6dRP2L1er2m/0uTxeEIGt5ICm5V5PJ6Q4zt27Gj1febn56u4uFglJSXKzc2VdPR9lpWVqby8vEu11tfXtztn+PDhXbo2AAAA0JrDhw/L4/HozTff1Jtvvqm33npLjY2NJ3TN+Ph4jRs3LiikPe+88zRkyJAwVQ0AAHqKurq6Nsc7kqmZJSLhbXZ2tmpqalRWVqZp06Zp5MiRQePl5eWdXk1rRnjb0YD5+PYHeXl5amhokNvtlnR0la3dbldBQUHQqtqqqiq5XC45nU4lJSXJ6/WqvLw8ZIuGjpgyZUq7c8xawQwAAIDu4+DBg6qsrAyEtW+//ba+/fbbLl8vISEhKKSdOHGizj77bPXt2zeMVQMAgJ4qJSXF7BK6LCLh7ahRo+T1epWYmNgiuJX+tVlXQUFBq6taj1VZWaknnngizFVGTnFxcYfm2e32Ds8FAAAAzLJ//3699957gbD2nXfe0b59+7p0rdTU1KCQ9rzzztOIESPYPAwAACCEiIS35eXlWrFiRasrSA3D0IIFC3Tttdd26Hpz5swxJbztSLBsJWvWrFFycrLZZQAAACDG7d27V++8804grH3vvfd04MCBTl9n9OjR+rd/+zc5HA5NnDhR48eP18CBAyNQMQAAQOtqa2vbHK+vr+/Qb7SbIWJd/bOyslodczgcgX6xHTVq1KgTLSnsmtsqNK8kNltycjI9bQEAANBpu3fv1ttvv60333xTq1ev1tq1a3Xo0KFOX+ess87SxRdfrIsvvlj/9m//pmHDhkWgWgAAgM6J5bzMlC1ZFy9e3OlzPv/88whU0j7DMOT1ekOONfe6PbaPLQAAAGBlfr9fdXV1qqys1D//+U+9+eab8ng8OnLkSKevNX78+KCw9rTTTotAxQAAAD2XKeFtazZv3iyfzyfDMCzz61QZGRkqKSmRz+dr0UahOdTNyckxoTIAAACE0tTUJJvNRg9VHQ1qv/rqK1VVVamysjLwddu2bZ2+VlxcnCZOnBgIar/3ve9p0KBBEagaAAAAzUwPbzdv3iyXy6WysrKg42lpaVq6dKnOO+88kyo7yuVyqaSkRMuXL1dubm7QWHl5uex2OytvAQAALGDv3r1atGiRHn30UTU1NenSSy/VjBkz9KMf/Uj9+/c3u7yo+Prrr4NC2qqqKm3durVL14qPj1daWlpgZe13v/tdJSQkhLliAAAAtMXm9/v9Zt38iSeeUF5enlorwWazqaioSPPnz49YDampqfJ6va3WIP0rwK2pqQmsvnW73crMzFRVVZWp4W1dXZ1SUlIkHW2+HMs9PAAAALrC7/errKxM8+fPD7kZRZ8+ffSDH/xAM2bM0L//+78rMTHRhCrDr76+vsWK2i1btnT5er1791Z6enogrL3wwgs1YMCAMFYMAABgTVbO10xbebtixQrl5ubK4XAoJydHdrs9sPFXQ0ODqqurVVpaqvz8fNntds2ePTts93a5XPJ4PGpoaAi0PkhNTZVhGDIMQ8XFxUHzCwsLlZ6eLqfTGdQ6obq6utMbrwEAACB8PvzwQ1133XV6/fXXW51z4MABvfzyy3r55ZfVq1cvXXLJJZoxY4Z+9rOfaejQoVGstuu2bNmiqqqqoLD266+/PqFrJiQkKC0tTd/97nf1b//2b7rgggt0yimnhKliAAAAhIMpK28bGxs1atQoLV26VFlZWW3OLSkpUUFBgWpqaizTB9dKrPyTAQAAgEjx+Xy67bbb9Mgjj3Rpoy3p6G95XXTRRZoxY4ZmzJihM844I8xVdl5TU5O++OILbdy4URs2bAgEtV999dUJXXfgwIFKS0vT5MmTA18Nw6AvMAAAgKydr5kS3hYUFCgpKUk33nhjh+YXFRWppqZGjz/+eIQriz1W/uYCAAAIt6amJv3xj3/UggUL9M0334ScM3XqVP3sZz/TK6+8otdff12HDx/u0LXT0tI0Y8YMZWVlaezYseEsO6SdO3dq48aN2rhxo95//31t3LhRH3zwgXbv3n1C1x0wYIAcDocmT54cCGtTU1MVFxcXpsoBAAC6Fyvna6aEt+np6Vq7dm3Ez+kJrPzNBQAAEE5r167Vb37zG7333nshx1NSUnT//fcrKysrsKJ0586d+utf/6qVK1fqtdde0/79+zt0r7PPPjuwInfixIkntEL14MGD2rRpU1BIu3HjRtXV1XX5ms369+8vh8MRtKp2zJgxBLUAAACdYOV8zZSet13ZJKK5Hy4AAAB6lm+++UYLFy7UU089FXKT2T59+ig/P18LFixo0bM1MTFRV155pa688kp9++23evXVV7Vy5Uq98sor+vbbb1u950cffaSPPvpId955p0aNGhUIcs8///xWg1G/36/a2toWIe2mTZs6vPq3Lf369dOkSZOCWh+ceeaZBLUAAADdmCnhbVdWLjQ0NESgEgAAAFjV4cOH9dhjj+mWW25RY2NjyDk//elPdf/993doE9n+/fvL6XTK6XRq//79qqio0IoVK/SXv/ylzb9r1tTU6L777tN9992n5ORk/fznP9eMGTPUt2/foJB248aNrdbZWXa7XePHjw8Ka8eOHav4+PiwXB8AAACxwZTwdseOHZ2a39jYGHKVBQAAALqnN954Q7/5zW/0wQcfhBw/88wz9eCDD+rSSy/t0vX79u2rH//4x/rxj3+sw4cPa/Xq1VqxYoVeeukl1dfXt3pefX29HnvsMT322GNduu/xevfurbPOOkvjx4/X+PHjNWHCBI0fP16nn346m4kBAADAnJ6399xzjxoaGrRo0aIOzZ83b54Mw+jwBmc9iZV7cgAAAHRWXV2dbrjhBi1btizkeP/+/XXzzTfr+uuv10knnRT2+zc1Nem9997TihUrtHLlStXU1ITt2iNGjAiEs82PsWPHqnfv3mG7BwAAADrPyvmaKeGtJI0ePVrTp09vc9XCrl27NGfOHHk8Hn322WdRrC52WPmbCwAAoKMOHDig++67T3fddZf27t0bcs4vfvELFRUVadiwYVGpye/3a8OGDYEg96OPPurQeQkJCUEB7YQJE3TuuecqISEhwhUDAACgK6ycr5kW3no8Hk2ePFk2m00ZGRkyDEN2u12S5PP55PV65Xa7JUnl5eWaOnWqGWVanpW/uQAAADrilVde0fXXX6/q6uqQ4xMnTtTDDz+s7373u1GuLNimTZv00ksvacWKFaqqqlKvXr00bty4oHYH48ePV0pKCi0PAAAAYoiV8zXTwlvpaIDrdDpVU1PT4i+4fr9fdrtdpaWlmjZtmkkVWp+Vv7kAAADa8tlnn+n666/X//3f/4UcT0xM1F133aXc3FzLbdR14MAB2Wy2iLRuAAAAQHRZOV+LM/PmDodD1dXVWrx4sSZNmiS/3y+/369Ro0YpPz9fNTU1BLcAAADdzLfffquFCxfq3HPPDRnc2mw25eXl6dNPP9W8efMsF9xKUp8+fQhuAQAAEHGmrrzFibPyTwYAAACOdejQIZWWlio/P19fffVVyDkXXnihHn74YTkcjihXBwAAgJ7KyvlaL7MLAAAAQPfV1NSkt956S88//7zKysq0Y8eOkPOGDh2qoqIi/fKXv6RfLAAAAPD/I7wFAAA4QR999JGeffZZ1dfXy2azKS4uTnFxcR163pl5vXr10jnnnKOLL75Y/fr1M/ttt8rv92vdunV64YUX9OKLL6qurq7Vub169dL111+vm2++WQMHDoxilQAAAID1WSK8feKJJ1ReXi6v1ytJMgxDs2bN0s9//nOTKwMAAGid3+/X448/ruuvv16HDh2K2n179+6tiy66SNOnT1dmZqYcDofi4kzdykCS9Omnn+qFF17QCy+8oE8++aTd+dOnT9eDDz6ocePGRaE6AAAAIPaY2vN28+bNcjqd8ng8ko7+A0hS4FflMjMztXz5clZhtMHKPTkAAOjO9u3bp7lz5+qZZ54xuxQNGjRI06ZNC4S5I0aMiNq9v/rqKy1btkzPP/+8qqqqOnTOBRdcoPz8fP30pz+lRQIAAABMZ+V8zbTwdt26dZo8eXIgsDUMQ4ZhSJIqKyvl8/kkSUlJSaqqqtIZZ5xhRpmWZ+VvLgAAuquamhplZWVp3bp1ZpcS0tixY5WZmanp06fr+9//vgYMGBDW6zc0NGjFihV6/vnn9eabb6ojf50cP368rrjiCs2aNUsjR44Maz0AAADAibByvmZaeDt69Gh5vV7l5+eroKBACQkJQeONjY26++67dc8992jy5Mlas2aNGWVanpW/uQAA6I5WrVqlyy+/XA0NDS3GfvnLX2rIkCFqampSU1OT/H5/u887Os/v92v79u1as2aNDh8+3OF6e/XqpQsuuCAQ5k6ePFnx8fGdft979uzRyy+/rOeff16vvfZah9pEjBw5UldccYUuv/xynXvuuZ2+JwAAABANVs7XTAlvFyxYoJKSEnk8nnZXXni9Xo0ePVpLly7V7Nmzo1NgDLHyNxcAAN2J3+/X4sWLddNNN7VYadq/f3/98Y9/1IwZMyJex+7du/XGG2+ovLxcq1at6lBv2WPZ7fagFgujRo1qde7Bgwf12muv6YUXXtBf/vIX7d27t93rDxkyRDNnztQVV1yh73znO7RFAAAAgOVZOV8zJbwdPXq0SkpKNHXq1A7Nd7vduueee/Taa69FuLLYY+VvLgAAuotdu3bpP/7jP/TnP/+5xdi4ceO0cuVKnXXWWdEvTNKXX34ZCHLdbnfIFcFtGT16dGBV7iWXXKIBAwZo9erVev7551VWVqadO3e2e42BAwcqKytLl19+uS655BL16mWJPXEBAACADrFyvmZaePv5559H/JyewMrfXAAAdAcfffSRZsyYEXKF689//nM9/fTTltlc9ciRI1q3bl0gzH377bc71N6gWXx8vBITE7V9+/Z25/bt21eXXXaZrrjiCv3whz9U3759T6R0AAAAwDRWztdMWRbRvDFZZzgcjghUAgAA0LoVK1boqquu0rfffht0PC4uTnfddZdcLpel2gLEx8dr8uTJmjx5sgoKCvTtt99q9erVWrVqlcrLy/XRRx+1ef6RI0faDG7j4+OVmZmpyy+/XD/72c8sE1oDAAAA3VW3+J22Xbt28Y8HAAAQNocPH9ZNN92koqKiFmNJSUl68cUXlZmZaUJlndO/f3/96Ec/0o9+9CNJR1cUuN3uQJjbkRW2knTRRRfpiiuuUHZ2tk477bRIlgwAAADgGKaEt3l5eXriiSd07bXXdmj+66+/rvT09FbHExMTdeTIkXCVBwAAerDt27dr1qxZqqioaDHmcDi0YsWKdjdctarhw4frqquu0lVXXaWmpiZt2LAhEOT+4x//0MGDBwNzJ0yYoCuuuEKzZs3SGWecYWLVAAAAQM9lSs9bSZo5c6ZuuukmnXfeeW3O27x5s/Ly8lrdrKyxsVGJiYlqamqKRJmWZ+WeHAAAxJrKykplZWXpyy+/bDF21VVX6bHHHtPJJ59sQmWRt3fvXr311lvauXOnzj33XJ1zzjlmlwQAAABEhZXzNVNW3hYUFCgpKUkOh0PZ2dlKSkoKOc/r9crtdisjI0Pz5s1rMd7Q0CCPx2OpXnMAACA2PfXUU/r1r3+tAwcOBB3v3bu3HnzwQc2dO7db/53jlFNO0fTp080uAwAAAMAxTFl5m5SUpMbGRoXr1jabrce2TbDyTwYAAIgFBw4c0H//93+ruLi4xVhycrLKysp04YUXmlAZAAAAgGiwcr5mysrb5pW2M2fOlN1u7/J1fD6f1q5dq/Xr14enMAAA0KPU1dUpOztb7733Xoux733ve1q+fLmGDh1qQmUAAAAAYFJ4a7fbtWDBgg5vWNae+Pj4sFwHAAD0HG+++aZmzpypb775psXYf//3f+uee+5R7969TagMAAAAAI6KM+OmhmG02ue2K0zacw0AAMQgv9+v3//+95o2bVqL4Pbkk0/Wc889pwceeIDgFgAAAIDpTFl5u3z58rBeb+fOnWG9HgAA6J727Nmja6+9Vi+++GKLMcMw9NJLL2nChAkmVAYAAAAALZkS3oZbQkKC2SUAAACL+/zzz/Xzn/9cH3zwQYuxH/7wh3ruueeUmJhoQmUAAAAAEJopbRMAAACi6ZVXXtHkyZNDBre33HKLXnnlFYJbAAAAAJbTLVbeAgAAtOaRRx7Rb37zmxbHExIS9Oyzz+onP/mJCVUBAAAAQPsIbwEAQLe1e/du3XDDDS2On3vuuVq5cqXGjBljQlUAAAAA0DG0TYgQr9eroqIipaamtjrH4/EoMzNTTqdTaWlpcjqd8ng8UawSAIDu7YMPPtCBAweCjuXk5Oidd94huAUAAABgeay8jQCn06n09HRVV1eroaEh5ByPx6NFixapvLw8cMzlciktLU1VVVVyOBzRKhcAgG7r448/Dnp95pln6oUXXpDNZjOpIgAAAADoOFbeRkBpaany8/PbXHW7aNEiGYYRdKywsFB2u10ulyvSJQIA0CMcH96ec845BLcAAAAAYgbhrUmSkpJCtkgwDENer9eEigAA6H6OD2/POusskyoBAAAAgM7r8W0TXC6XysrKVF1d3eY8t9utwsJCGYYRaIXQ/LoriouLWxzz+XzyeDzKzc3t0jUBAEAwwlsAAAAAsaxHhrdOp1M+n0+GYWj58uXtzi8qKlJxcbGqqqpkt9slHQ1z09LSVFFREbb+tC6XS3a7XYWFhWG5HgAAPdn+/ftVU1MTdIzwFgAAAEAs6ZHhbWlpaeB5ZWVlm20KvF6vXC6XSktLA8GtJGVkZCgjI0NOp7PdVbsdUVRUpMrKStXU1ATdBwAAdM2nn34qv98fdGzcuHEmVQMAAAAAnRf2nrcrV64M9yVNVVZWJuloWHu8nJwceb3ekL1rO8Plcqm6ujpoZS8AADgxx7dMGDFihPr162dSNQAAAADQeWEPb51OZ7gvaaply5ZJUshQtflY85yuyMvLU3p6elAP3O72vyEAAGag3y0AAACAWBf2tgl+v18bNmzQeeedF+5Lm8Lj8bS6GrZ5s7LWVt7u2LFDPp+v1WtnZmbKbrfL6/WqqKgocE5X1dfXtztn+PDhXb4+AACx5PjwlpYJAAAAQM9UV1fX5nhHMjWzhD28tdvtmjNnjtasWRPuS0ddW8HrsRoaGoJe5+XlqaGhQW63W9K/QtqCgoLA5mZOpzMw3tyaoVlXNyybMmVKu3OO7/0HAEB3xcpbAAAAAJKUkpJidgldFpENyyorKzVo0CDNnDlTmZmZysjI0MCBAyNxK0s6tgVCa47dNA0AAITXkSNH9OmnnwYdI7wFAAAAEGsiEt66XC4tWLBAlZWVKi8v15IlS7Rz505Nnjw5psLcWNs8bM2aNUpOTja7DAAATFdTU6MDBw4EHSO8BQAAAHqm2traNsfr6+s79BvtZgh7eOvz+VRQUKCBAwdq2rRpmjZtWmBs3bp1crvdMRvmHq+5rUJSUpK5hfz/kpOT6WkLAIBatkwYNGiQBg8ebFI1AAAAAMwUy3lZ2MPb/Pz8VoPYSZMmadKkSbrxxhslxUaYaxiGvF5vyLHmXrfNfWwBAIA10O8WAAAAQHcQF+4LLl68uMNzm4PcVatWae3atcrNzVV1dbWcTqfGjBmjefPmaeXKldq8eXO4y+ywjIwMSaE3L2sOdXNycqJZEgAAaAfhLQAAAIDuIOzh7YmYNGmSHA6HEhISVF1drZKSEjmdTqWmpio9Pd2UmlwulyRp+fLlLcbKy8tlt9tZeQsAgMUQ3gIAAADoDiwR3u7atUv33nuvxowZo+nTp2vFihWSJL/fr1GjRmnx4sVyu90RubfP5wu5qraZYRjKz8+Xy+UKmud2u1VWVqaKioqI1AUAALrG7/cT3gIAAADoFsLe87YzXn/9dRUXF6usrEzS0X9sNcvOzlZeXl7Qhmfh4nK55PF41NDQEGh9kJqaKsMwZBiGiouLg+YXFhYqPT1dTqdTdrs9cLy6ulqGYYS9PgAA0HX19fXatWtX0DHCWwAAAACxKOrh7a5du1RSUqLi4uJAcNoc2hqGoby8POXm5iohISFiNRQWFnb6nOzsbGVnZ0egGgAAEE6bNm0Ken3KKacoJSXFpGoAAAAAoOuiFt62t8q2oKBAkyZNilY5AACgmzq+ZcK4ceMUF2eJTlEAAAAA0CkRDW+bV9kuWrQo0C/22FW2LpdLM2fOjOgqWwAA0LPQ7xYAAABAdxGR8Pb1119XYWFhYJOxY1fZ5ubmKi8vj1W2AAAgIkKtvAUAAACAWBT28HbMmDEtetk6HA7l5eVpzpw54b4dAABAEFbeAgAAAOguwh7eVldXy2azye/3s8oWAABEVWNjo+rr64OOEd4CAAAAiFURaZvg9/vlcrmUk5OjiRMnRuIWAAAALRy/6jY+Pl6jR482qRoAAAAAODERCW+rqqrk9Xq1ZMkSVVZWatCgQcrMzFRGRgZhLgAAiJjjw9vRo0frpJNOMqkaAAAAADgxYQ9vbTabJk2apEmTJikrK0vS0V9hdLvdJxTm3nvvvbrhhhvCXS4AAOhG6HcLAAAAoDsJe3g7atSoFscSEhKUlZXV5TC3sbFRLpeL8BYAALSJ8BYAAABAdxL28Pbzzz9vd05nwlzDMFRSUhLuMgEAQDdEeAsAAACgO4lIz9vOaivMXb58uRobG2W3280tEgAAWNr+/ftVU1MTdIzwFgAAAEAsizO7gFCaw9wlS5aooaFBEydOlM/nM7ssAABgYZ9++qmampqCjo0bN86kagAAAADgxFkyvD3e0qVLzS4BAABY3KZNm4Jep6SkqH///iZVAwAAAAAnLibCW4fDIb/fb3YZAADAwuh3CwAAAKC7iYnwVpJKS0vNLgEAAFgY4S0AAACA7iZmwtvmzcwAAABCOT68pd8tAAAAgFgXM+EtAABAa44cOaJPPvkk6BgrbwEAAADEOsJbAAAQ8zZv3qwDBw4EHSO8BQAAABDrCG8BAEDMO75lQlJSkgYPHmxSNQAAAAAQHoS3AAAg5oXarMxms5lUDQAAAACEB+EtAACIeaHCWwAAAACIdYS3AAAg5hHeAgAAAOiOCG8BAEBM8/v9hLcAAAAAuiXCWwAAENO2bNmixsbGoGOEtwAAAAC6A8JbAAAQ045fdXvKKadoxIgRJlUDAAAAAOFDeAsAAGLa8eHt2LFjFRfHX3EAAAAAxD7+ZQMAAGLapk2bgl7TMgEAAABAd0F4CwAAYhqblQEAAADorkwJb3ft2qV58+bpySefNOP2AACgGzk+vB03bpxJlQAAAABAeJkS3mZnZ6u4uFi5ublm3B4AAHQTjY2N+vrrr4OOsfIWAAAAQHfRy4ybNjQ0yOFwaPLkyWbcHgAAdBPH97uNj4/XmDFjTKoGAAAAAMLLlJW3SUlJqqys1JIlSzp8Tk5OTgQrAgAAsej4lgmpqak66aSTTKoGAAAAAMLLlPDW6XTq3nvv7dQ5ZWVlEaoGAADEKjYrAwAAANCdmRLezpkzR36/XwUFBdq8eXO78xsbGyNfFAAAiDmEtwAAAAC6M1N63q5cuVKpqanasWOH0tLSZBhG4BGK2+2OcoUAACAWEN4CAAAA6M5MCW+vvfbawGpav9+vqqoqVVVVhZxrs9nk9/tls9miWWJUeL1eFRYWBr12uVzKyMgwsSoAAGLD/v375fV6g44R3gIAAADoTkwJb5OSkiRJM2fOlN1ub3d+eXm51q9fH9mioszn88nlcqm0tDToeFpampYuXSqHw2FSZQAAxIbPPvtMTU1NQcfGjRtnUjUAAAAAEH6mhLd2u11z587VDTfc0KH5ixcvVnx8fISrii632y2fz9fieE5OjtxuN+EtAADtOL5lwvDhwzVgwACTqgEAAACA8DNlw7K2+tu2xu/3R6gaczgcDrndbjmdzqBf+Vy2bJmys7NNrAwAgNhAv1sAAAAA3Z0pK2+XL1/e6XN27twZgUo6zuVyqaysTNXV1W3Oc7vdKiwslGEYamhokKTA62MZhqHCwsLAdXNzc9XQ0KDS0tJOB9sAAPREmzZtCnpNeAsAAACguzElvG3N5s2b5fP5ZBiGBg4cGDSWkJAQ9XqcTmegno4EzkVFRSouLlZVVVWgl6/b7VZaWpoqKipatELIzc1VeXm5GhoaVFJSIklKT09Xfn5+2N8LAADdDStvAQAAAHR3prRNONbmzZuVk5Oj+Ph4paamKi0tTYmJiZoyZYo2bNhgam2lpaUqLy9XcXFxu6thvV6vXC6XCgsLgzZhy8jIUEZGhpxOZ9B8j8ejadOmBcLeqqoqORwOuVwuuVyuSLwdAAC6jSNHjuiTTz4JOsZmZQAAAAC6G1PD2yeeeEKpqakqLS2V3+8PelRWVsrhcOi+++4zs8QOKysrk3Q0rD1eTk6OvF6vPB5P4NicOXOC2ik4HA5VVVUpPz8/sAoXAACE9sUXX2j//v1Bx1h5CwAAAKC7Ma1twooVK5SbmyuHw6GcnBzZ7XYlJSVJkhoaGlRdXa3S0lLl5+fLbrdr9uzZZpXaIcuWLZOkoFW3zZqPLVu2LNA6obkdw/EKCgq6HN7W19e3O2f48OFdujYAAFZyfMuExMREnXbaaSZVAwAAAMDK6urq2hzvSKZmFlPC28bGRs2ZM0elpaXKyspqdd7ixYtVUlKi/Px8OZ3OFn1wrcTj8YQMbiUFQtpjV97m5eUpLy9P5eXlQXMXLVqkwsLCLtUwZcqUduf4/f4uXRsAACsJ1e/WZrOZVA0AAAAAK0tJSTG7hC4zJbxdvHixCgoK2gxum+Xm5srn88nlcunxxx+PQnWd5/P5OjSvoaEh8Dw/P1+GYcjpdCopKUkNDQ3y+XzKy8tTdnZ2hCoFAKB7YLMyAAAAAD2BKeGt2+3W2rVrOzw/Pz9f6enpEazIHNnZ2WENatesWaPk5OSwXQ8AAKsivAUAAADQUbW1tW2O19fXd+g32s1gSnibmJjY6XOa++FaUWvtEqItOTmZnrYAgG7P7/cT3gIAAADosFjOy+LMuGlXetId23Ig1jS3VbByAA0AQKzYunVri5ZFhLcAAAAAuiNTwtsdO3Z0an5jY6PlN9oyDKPV3rfNwbPD4YhiRQAAdE/Hr7o9+eSTdcYZZ5hUDQAAAABEjinhbU5OjgoKCjo8f8GCBcrJyYlgRScuIyNDUujNy7xeryRZ/j0AABALjg9vx44dq7g4U/5KAwAAAAARZcq/dG688UaVlpbq17/+dZvzdu3apZycHLndbt14441Rqq5rXC6XJGn58uUtxsrLy2W321l5CwBAGNDvFgAAAEBPYcqGZdLRkHPy5MkqLi5WRkaGDMMIbPzl8/nk9XrldrslHQ0/zebz+VptiyAdbZuQn58vl8ulmTNnBt6L2+1WWVmZqqqqolMoAADd3KZNm4JeE94CAAAA6K5MC28dDocqKyvldDpVXl7eYhMzv98vu92u0tJSTZ061ZQaXS6XPB6PGhoaAq0PUlNTZRiGDMNQcXFx0PzCwkKlp6fL6XQGwltJqq6ulmEY0SwdAIBu6/iVt+PGjTOpEgAAAACILJs/AjuBbd68WT6fTxMnTuzQ/KKiIi1fvlwej0fS0VWs2dnZKigoUEJCQrjL61bq6uqUkpIiSaqtrdXw4cNNrggAgMjZtWtXi78bbNy4Ueeee65JFQEAAACIdVbO18K+8nbFihWaOXOmbDabli9frhkzZrR7Tn5+vvLz88NdCgAA6GaOb5kQFxenMWPGmFQNAAAAAERW2DcsKy4uVkJCgpqamoJaBxzr3nvvDfdtAQBAD3B8y4TU1FT16dPHpGoAAAAAILLCHt7abDY1NDSourq61V61Lper09dNT08/0dIAAECMOz68ZbMyAAAAAN1Z2MNbv9+v3bt3a9SoUW3O6azmfrgAAKDnIrwFAAAA0JOEPbzNyMiQw+HQhg0bWp1js9k6dc2ampoTLQsAAHQDhLcAAAAAepKwb1iWn5+v4uJiORwOGYYhwzBa9L71+/36wQ9+0OFrVlZWhrlKAAAQaw4cOKDq6uqgY4S3AAAAALqzsIe3klRdXS2n06kVK1a0+EdWs/Ly8k5ds7OrdQEAQPfy2WefqampKejYuHHjTKoGAAAAACIvIuGtJJWWlqqxsVGVlZXyer2B436/X/PmzdOSJUs6fK3Kyko98cQTkSgTAADEiONbJpx++ukaOHCgSdUAAAAAQOTZ/F3ZPewExcfH68iRIxE/pyeoq6tTSkqKJKm2tlbDhw83uSIAACLjjjvu0K233hp4nZGR0enf5AEAAACA41k5Xwv7hmUd0ZW8eNSoURGoBAAAxAo2KwMAAADQ05gS3h7fr64jPv/88whUAgAAYgXhLQAAAICexpTwFgAAoDOampr0ySefBB1jszIAAAAA3R3hLQAAsLwvvvhC+/fvDzrGylsAAAAA3R3hLQAAsLzjWybY7XYNGTLEpGoAAAAAIDoIbwEAgOWF6ndrs9lMqgYAAAAAooPwFgAAWB6blQEAAADoiQhvAQCA5RHeAgAAAOiJCG8BAICl+f1+wlsAAAAAPRLhLQAAsLRvvvlGO3fuDDpGeAsAAACgJyC8BQAAlnb8qtu+ffvqjDPOMKkaAAAAAIgewlsAAGBpx4e3Y8eOVXx8vEnVAAAAAED0EN4CAABLo98tAAAAgJ6K8BYAAFga4S0AAACAnipmwtv169ebXQIAADAB4S0AAACAnipmwluXy2V2CQAAIMp2796tr776KujYuHHjTKoGAAAAAKKrl9kFSNLcuXO1c+fOFseXLVsWeL527Vr94Ac/kN1uDxzLy8vT1KlTo1EiAAAwwaZNm4Jex8XF6cwzzzSpGgAAAACILkuEt/n5+Zo+fbq8Xq8Mw1BeXp6ys7NbzCsvLw88T0tLI7gFAKCbO75lgmEY6tOnj0nVAAAAAEB0WSK8NQxDLpdLVVVVWrJkSavziouLJUk+n09utzta5QEAAJPQ7xYAAABAT2aJ8LampkZutzuoTcLxJk+erDlz5gReG4ahJ554Qtdee200SgQAACYgvAUAAADQk1liw7KioiItXry4U+dkZWUFtVEAAADdD+EtAAAAgJ7MEuFtZWWlRo0a1eacwsLCFseSkpIiVRIAADDZwYMHVV1dHXSM8BYAAABAT2KJ8LYjJk2a1OKY1+s1oRIAABANn332mY4cORJ0bNy4cSZVAwAAAADRZ4nw1ufzdek8wlsAALqv41smDBs2TAkJCSZVAwAAAADRZ4nwdtSoUVq/fn2nzlm3bh3/gAMAoBuj3y0AAACAns4S4W12drZcLlenzlmwYIFmzZoVoYrM4XQ6VVZWZnYZAABYAuEtAAAAgJ7OEuFtbm6uqqurdd9993Vo/tKlS1VZWakbbrghwpVFT0lJicrKytTQ0GB2KQAAWALhLQAAAICezhLhrSQtWbJEN954o2bNmqXNmzeHnLNr1y7NmzdPc+fO1dKlS6NbYAR5PJ4Wu2kDANCTNTU16ZNPPgk6RngLAAAAoKfpZXYBzTIyMrR48WItWLBApaWlMgwj8GhoaJDX65XH45EkzZkzRzNmzDC54vBZtGiRSktLVVRUZHYpAABYwhdffKF9+/YFHRs3bpxJ1QAAAACAOSwT3kpSfn6+DMPQnDlzVF1drerqatlsNvn9/sCcwsJC3XjjjVGvzeVyqaysrN0Vsm63W4WFhYHQWVLgdSh5eXkqLCwMe70AAMSyTZs2Bb1OSEjQ0KFDTaoGAAAAAMxhqfBWOrp5WXZ2tlasWKHy8nI1NDQoKSlJaWlpmjlzphISEqJWi9PplM/nk2EYWr58ebvzi4qKVFxcrKqqKtntdklHw9y0tDRVVFTI4XAEzS8pKVFmZmarwS4AAD1VqH63NpvNpGoAAAAAwByWC2+bZWVlKSsry9QaSktLA88rKyvl9Xpbnev1euVyuVRaWhoIbqWj7SAyMjLkdDqDVu16vV5VV1crNzc3IrUDABDL2KwMAAAAACy0YVmsKysrk3Q0rD1eTk5OUM9e6WgbBtolAAAQGuEtAAAAAFhk5e3cuXO1c+fOoGNJSUl6/PHHA69XrFihmpoaZWRkaOLEiVGusH3Lli2TpKBVt82ajy1btkwOhyOwgtfpdAbm+Hw+SVJxcbHKy8tVUFDQos0CAAA9gd/vJ7wFAAAAAFkkvM3Pz9f06dPl9XplGIby8vKUnZ0dNCcrK0sVFRVasmSJEhMTtWjRIpOqDc3j8YQMbiUFeto2r7w1DCOoJYN0NLxNTExUXl5el1sp1NfXtztn+PDhXbo2AADRsm3btsCmn80IbwEAAAB0VV1dXZvjHcnUzGKJ8LY5sK2urtaSJUtanTdt2jRNmzZNK1asUEFBgWUC3OZVs+05/h+izfLy8gKrcQsLC1VeXq7CwsJOb2Q2ZcqUduf4/f5OXRMAgGg7ftVtnz59NHLkSHOKAQAAABDzUlJSzC6hyywR3tbU1KiysjLQeqA9WVlZWrt2rdavX2/JFgqdVVxcbHYJAABYxvHh7dixYxUfH29SNQAAAABgHkuEt0VFRVq8eHGnzikoKNCCBQuC+uKapbV2CdG2Zs0aJScnm10GAAAnhH63AAAAAMKptra2zfH6+voO/Ua7GSwR3nq9Xo0aNapT5yQkJLTahsBqmtsqJCUlRfQ+ycnJ9LQFAMQ8wlsAAAAA4RTLeVmc2QWciI72mo0GwzBarac5ZHY4HFGsCACA2ER4CwAAAABHWSK8bd6sq7OstPI2IyNDUuhAufn95eTkRLMkAABizu7du1vsBEt4CwAAAKCnskR4O2rUKK1fv75T56xbty7ibQg6w+VySZKWL1/eYqy8vFx2u52VtwAAtGPTpk1Br+Pi4jRmzBiTqgEAAAAAc1kivM3IyAiEnx21ePFiZWZmRqiilnw+X5ttGgzDUH5+vlwuV9A8t9utsrIyVVRURL5IAABi3PHh7ahRo9S3b1+TqgEAAAAAc1liw7L8/HyVlJToySef1OzZs9udv3TpUnk8Hi1btiyidblcLnk8HjU0NARaH6SmpsowDBmGoeLi4qD5hYWFSk9Pl9PplN1uDxyvrq6WYRgRrRUAgO6AfrcAAAAA8C+WCG8lacmSJZo+fbqqqqqUn5+vkSNHtpizefNmFRYWqqSkROXl5RGvqbCwsNPnZGdnKzs7OwLVAADQ/RHeAgAAAMC/WCa8zcjI0I033qh77rlHxcXFMgxDDodDSUlJamhokMfjCax+vfHGGzV16lSTKwYAAOFGeAsAAAAA/2KZ8FY6utI1NTVVLpdL1dXVqq6uls1mk9/vlyTZ7XYVFhZqzpw5JlcKAADC7eDBg/r888+DjhHeAgAAAOjJLBXeSlJubq5yc3O1YsUKlZeXq6GhQUlJScrMzFRWVpbZ5QEAgAj5/PPPdeTIkaBjhLcAAAAAejLLhbfNsrKyCGuBGNLU1KS4uDizywAQw45vmZCcnKyEhASTqgEAAAAA80U9adm1a1e0bwkggl577TVNnDhR8fHxmjBhgubPn6/XXntNe/fuNbs0ADGGfrcAAAAAECzi4e369es1b948DRo0SPHx8UpMTFR8fLzGjBmjnJwcvfTSS5EuAUAEfPnll8rKytKll16qDRs2SJI2btyo+++/X5deeqkSExOVkZGhwsJCeTweNTU1mVwxAKsjvAUAAACAYBENb3NycpSWlqaSkhLt3LlTfr8/8PB6vSorK1N2drbi4+O1cOHCSJYCIEwOHDigu+++W+PGjdPKlStbnXfw4EFVVFRowYIFSktL05AhQ3T55ZfrqaeeUm1tbRQrBhArCG8BAAAAIJjN7/f7I3HhMWPGqLq6WpJkGEbg0dDQIK/XK4/HE1yIzabExEQtXbpUP//5zyNRUrdUV1enlJQUSVJtba2GDx9uckXozl577TX95je/0WeffXbC1xo3bpymT5+uzMxMff/731f//v3DUCGAWNXU1KT+/ftr3759gWMVFRWaOnWqiVUBAAAA6AmsnK9FZMOynJwcVVdXKzc3V4WFha1uNlJRUaHy8nKVlJTI5/OpoaFB2dnZKioq0vz58yNRGoAu+PLLL/U///M/ra60PfXUU3XzzTeroaFB5eXleu+991rsGH+8TZs2adOmTXrooYfUu3dvXXDBBcrMzNT06dOVlpam+Pj4SLwVABb15ZdfBgW3EitvAQAAACDsK2/XrVuntLQ0ud3uTq2WKSsr0+LFi+XxeGSz2ZSXl6fHHnssnKV1S1b+yQBi34EDB3TffffpzjvvbBGqSEdXzM+bN0+/+93vlJSUFDje2Niov//97yovL9eqVav0+eefd+q+iYmJmjZtmjIzM5WZmalRo0ad8HsBYG2vvvqqfvSjHwVeDxw4UD6fTzabzcSqAAAAAPQEVs7Xwh7ezp07V5K0ZMmSLp1fUlKiuXPnymazsQK3A6z8zYXY1l6LhPPPP1+PPvqoHA5Hu9favHlzIMitqKjQzp07O1XL6NGjA6tyf/jDH6pPnz6dOh+A9d1///1B/5//ne98R++++66JFQEAAADoKaycr4V9w7KKigoVFRV1+fzc3Fw1NDRo5MiRys/P10svvRTG6gC058svv1RWVpYuvfTSkMHtqaeeqieffFJvv/12h4JbSRo5cqTmzJmj0tJSbdu2Te+9957uvPNOXXzxxerdu3e753/++ed6/PHH9fOf/1yjR4/Www8/HHIlMIDYtWnTpqDXtEwAAAAAgAiEt36/XwMHDjyha9jtdnk8Hk2cOFFz5swJU2UA2nLgwAHdfffdGjduXMjetjabTb/+9a/1ySef6JprrlFcXNf++IiPj9eUKVN000036Y033lBDQ4NeeeUV/fd//3eHwpq6ujpdd911MgxD999/v/bs2dOlOgBYy8cffxz0mvAWAAAAACIQ3hqGEZbrJCQkqKKiQk1NTVq4cGFYrgkgtNdee03jx4/XTTfdFHJF6/nnn6/Kyko9+uijQb1tw6F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      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 443,
       "width": 695
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Author: Jake VanderPlas\n",
    "# License: BSD\n",
    "#   The figure produced by this code is published in the textbook\n",
    "#   \"Statistics, Data Mining, and Machine Learning in Astronomy\" (2013)\n",
    "#   For more information, see http://astroML.github.com\n",
    "#   To report a bug or issue, use the following forum:\n",
    "#    https://groups.google.com/forum/#!forum/astroml-general\n",
    "from scipy.stats import cauchy, norm\n",
    "from scipy import integrate\n",
    "\n",
    "#----------------------------------------------------------------------\n",
    "# This function adjusts matplotlib settings for a uniform feel in the textbook.\n",
    "# Note that with usetex=True, fonts are rendered with LaTeX.  This may\n",
    "# result in an error if LaTeX is not installed on your system.  In that case,\n",
    "# you can set usetex to False.\n",
    "from astroML.plotting import setup_text_plots\n",
    "setup_text_plots(fontsize=8, usetex=True)\n",
    "\n",
    "\n",
    "def logL_cauchy(xi, gamma, mu,\n",
    "                mu_min=-10, mu_max=10, sigma_min=0.01, sigma_max=100):\n",
    "    \"\"\"Equation 5.74: cauchy likelihood\"\"\"\n",
    "    xi = np.asarray(xi)\n",
    "    n = xi.size\n",
    "    shape = np.broadcast(gamma, mu).shape\n",
    "\n",
    "    xi = xi.reshape(xi.shape + tuple([1 for s in shape]))\n",
    "\n",
    "    prior_normalization = - (np.log(mu_max - mu_min)\n",
    "                             + np.log(np.log(sigma_max / sigma_min)))\n",
    "\n",
    "    return (prior_normalization\n",
    "            - n * np.log(np.pi)\n",
    "            + (n - 1) * np.log(gamma)\n",
    "            - np.sum(np.log(gamma ** 2 + (xi - mu) ** 2), 0))\n",
    "\n",
    "\n",
    "def logL_gaussian(xi, sigma, mu,\n",
    "                  mu_min=-10, mu_max=10, sigma_min=0.01, sigma_max=100):\n",
    "    \"\"\"Equation 5.57: gaussian likelihood\"\"\"\n",
    "    xi = np.asarray(xi)\n",
    "    n = xi.size\n",
    "    shape = np.broadcast(sigma, mu).shape\n",
    "\n",
    "    xi = xi.reshape(xi.shape + tuple([1 for s in shape]))\n",
    "\n",
    "    prior_normalization = - (np.log(mu_max - mu_min)\n",
    "                             + np.log(np.log(sigma_max / sigma_min)))\n",
    "\n",
    "    return (prior_normalization\n",
    "            - 0.5 * n * np.log(2 * np.pi)\n",
    "            - (n + 1) * np.log(sigma)\n",
    "            - np.sum(0.5 * ((xi - mu) / sigma) ** 2, 0))\n",
    "\n",
    "\n",
    "def calculate_odds_ratio(xi, epsrel=1E-8, epsabs=1E-15):\n",
    "    \"\"\"\n",
    "    Compute the odds ratio by perfoming a double integral\n",
    "    over the likelihood space.\n",
    "    \"\"\"\n",
    "    gauss_Ifunc = lambda mu, sigma: np.exp(logL_gaussian(xi, mu, sigma))\n",
    "    cauchy_Ifunc = lambda mu, gamma: np.exp(logL_cauchy(xi, mu, gamma))\n",
    "\n",
    "    I_gauss, err_gauss = integrate.dblquad(gauss_Ifunc, -np.inf, np.inf,\n",
    "                                           lambda x: 0, lambda x: np.inf,\n",
    "                                           epsabs=epsabs, epsrel=epsrel)\n",
    "    I_cauchy, err_cauchy = integrate.dblquad(cauchy_Ifunc, -np.inf, np.inf,\n",
    "                                             lambda x: 0, lambda x: np.inf,\n",
    "                                             epsabs=epsabs, epsrel=epsrel)\n",
    "\n",
    "    if I_gauss == 0:\n",
    "        O_CG = np.inf\n",
    "        err_O_CG = np.inf\n",
    "    else:\n",
    "        O_CG = I_cauchy / I_gauss\n",
    "        err_O_CG = O_CG * np.sqrt((err_gauss / I_gauss) ** 2)\n",
    "\n",
    "    return (I_gauss, err_gauss), (I_cauchy, err_cauchy), (O_CG, err_O_CG)\n",
    "\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# Draw points from a Cauchy distribution\n",
    "np.random.seed(44)\n",
    "mu = 0\n",
    "gamma = 2\n",
    "xi = cauchy(mu, gamma).rvs(100)\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# compute the odds ratio for the first 10 points\n",
    "((I_gauss, err_gauss),\n",
    " (I_cauchy, err_cauchy),\n",
    " (O_CG, err_O_CG)) = calculate_odds_ratio(xi[:10])\n",
    "\n",
    "print(\"Results for first 10 points:\")\n",
    "print(\"  L(M = Cauchy) = %.2e +/- %.2e\" % (I_cauchy, err_cauchy))\n",
    "print(\"  L(M = Gauss)  = %.2e +/- %.2e\" % (I_gauss, err_gauss))\n",
    "print(\"Bayesian odds ratio of Cauchy-versus-Gaussian Models = %.3g +/- %.3g\" % (O_CG, err_O_CG))\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# calculate the results as a function of number of points\n",
    "Nrange = np.arange(1, 101, 2)\n",
    "Odds = np.zeros(Nrange.shape)\n",
    "for i, N in enumerate(Nrange):\n",
    "    res = calculate_odds_ratio(xi[:N])\n",
    "    Odds[i] = res[2][0]\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# plot the results\n",
    "fig = plt.figure(figsize=(8, 5))\n",
    "fig.subplots_adjust(hspace=0.1)\n",
    "\n",
    "ax1 = fig.add_subplot(211, yscale='log')\n",
    "ax1.plot(Nrange, Odds, '-k')\n",
    "ax1.set_ylabel(r'$O_\\mathrm{CG}$ for $N$ points', fontsize=12)\n",
    "ax1.set_xlim(0, 100)\n",
    "ax1.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax1.yaxis.set_major_locator(plt.LogLocator(base=10000.0))\n",
    "ax1.set_ylim(1e-3, 1e24)\n",
    "\n",
    "ax2 = fig.add_subplot(212)\n",
    "ax2.scatter(np.arange(1, len(xi) + 1), xi, lw=0, s=16, c='k')\n",
    "ax2.set_xlim(0, 100)\n",
    "ax2.set_xlabel('Sample Size $N$', fontsize=12)\n",
    "ax2.set_ylabel('Sample Value', fontsize=12)\n",
    "\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The odds ratio for the first 10 points is very close to unity ($O_{CG} = 1.45$) and is therefore inconclusive.\n",
    " \n",
    "***Why do we get an inconclusive odds ratio?*** \n",
    "- With only 10 points, the probability of drawing at least one point far away from the mean, which would strongly argue against the Gaussian model, is fairly small. \n",
    "- As the number of data values is increased, the ability to discriminate between the models increases, too. \n",
    "- As the above figure shows, when we increase the size of the observed sample, the odds ratio quickly favors the  Cauchy over the Gaussian model.\n",
    "- But things are not always that nice in realistic scenario. Careful that if you don't not know your models well enough things can go terribly wrong as you increase the number of datapoints (for examples in my field of ressearch see [Zimmerman et al 2019](https://arxiv.org/abs/1903.11008) and [Moore et al 2021](https://arxiv.org/abs/2103.16486))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you look at the code above... it's kind of nasty: there are numerical integrals etc. Unfortuntately this is generic: computing Bayesian evidences is a pain in the neck. Not even MCMCs are enough! \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Example of Coin Flip Bayesian Model Comparison <a class=\"anchor\" id=\"twob\"></a>\n",
    "\n",
    "Let's look at an example using coin flips. Let's assume we have $N$ draws and $k$ are \"success\" (say, heads). \n",
    "\n",
    "We will compare two hypotheses:\n",
    "\n",
    "- **M1**: We know the guy. The coin has a known heads probability $b_\\ast$ (say, a fair coin with $b_\\ast=0.5$), with a prior given by a delta function, $\\delta(b-b_\\ast)$,\n",
    "- **M2**: They are cheating. The heads probability $b$ is unknown, with a uniform prior in the range 0–1.\n",
    "\n",
    "Basically in **M1** we know about the fairness of the coin. In **M2** we don't know anything about the fairness of the coin.\n",
    "\n",
    "The model that we need (parametrized by the probability of success $b$, with $k$ successes) is the *binomial distribution*:\n",
    "\n",
    "  $$    p(k\\,|\\,b, N) = \\frac{N!}{k! \\, (N-k)!} \\, b^k \\, (1-b)^{N-k} $$\n",
    "\n",
    "For model **M2** the prior for $b$ is flat in the range 0-1 and the product of the data likelihood and prior is same as above. However, for model **M1** the prior is a  delta function $\\delta(b-b_\\ast)$ and we get for the product of the data likelihood and prior (which picks out $b=b_\\ast$) \n",
    "\n",
    "$$    p(k\\,|\\,b_\\ast, N, M1)\\,p(b|M1, I) = \\frac{N!}{k! \\, (N-k)!} \\, b_\\ast^k \\, (1-b_\\ast)^{N-k}. $$\n",
    "\n",
    "Consequently, the **odds ratio** is given by \n",
    "\n",
    "$$ O_{21} = \\int_0^1 \\left(\\frac{b}{b_\\ast}\\right)^k \\left(\\frac{1-b}{1-b_\\ast}\\right)^{N-k} db, $$\n",
    "\n",
    "as illustrated in the following figure. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 451,
       "width": 913
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Author: Jake VanderPlas\n",
    "# License: BSD\n",
    "#   The figure produced by this code is published in the textbook\n",
    "#   \"Statistics, Data Mining, and Machine Learning in Astronomy\" (2013)\n",
    "#   For more information, see http://astroML.github.com\n",
    "#   To report a bug or issue, use the following forum:\n",
    "#    https://groups.google.com/forum/#!forum/astroml-general\n",
    "import numpy as np\n",
    "from scipy import integrate\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "#----------------------------------------------------------------------\n",
    "# This function adjusts matplotlib settings for a uniform feel in the textbook.\n",
    "# Note that with usetex=True, fonts are rendered with LaTeX.  This may\n",
    "# result in an error if LaTeX is not installed on your system.  In that case,\n",
    "# you can set usetex to False.\n",
    "if \"setup_text_plots\" not in globals():\n",
    "    from astroML.plotting import setup_text_plots\n",
    "setup_text_plots(fontsize=14, usetex=True)\n",
    "\n",
    "\n",
    "@np.vectorize\n",
    "def odds_ratio(n, k, bstar):\n",
    "    \"\"\"Odds ratio between M_2, where the heads probability is unknown,\n",
    "    and M_1, where the heads probability is known to be `bstar`, evaluated\n",
    "    in the case of `k` heads observed in `n` tosses.\n",
    "\n",
    "    Eqn. 5.25 in the text\n",
    "    \"\"\"\n",
    "    factor = 1. / (bstar ** k * (1 - bstar) ** (n - k))\n",
    "    f = lambda b: b ** k * (1 - b) ** (n - k)\n",
    "\n",
    "    return factor * integrate.quad(f, 0, 1)[0]\n",
    "\n",
    "#------------------------------------------------------------\n",
    "# Plot the results\n",
    "fig = plt.figure(figsize=(10, 5))\n",
    "fig.subplots_adjust(left=0.13, right=0.95, wspace=0.05, bottom=0.15)\n",
    "\n",
    "subplots = [121, 122]\n",
    "n_array = [10, 20]\n",
    "\n",
    "linestyles = ['-k', '--b']\n",
    "bstar_array = [0.5, 0.1]\n",
    "\n",
    "for subplot, n in zip(subplots, n_array):\n",
    "    ax = fig.add_subplot(subplot, yscale='log')\n",
    "    k = np.arange(n + 1)\n",
    "\n",
    "    # plot curves for two values of bstar\n",
    "    for ls, bstar in zip(linestyles, bstar_array):\n",
    "        ax.plot(k, odds_ratio(n, k, bstar), ls,\n",
    "                label=r'$b^* = %.1f$' % bstar)\n",
    "\n",
    "    if subplot == 121:\n",
    "        ax.set_xlim(0, n - 0.01)\n",
    "        ax.set_ylabel(r'$O_{21}$')\n",
    "        ax.legend(loc=2)\n",
    "    else:\n",
    "        ax.set_xlim(0, n)\n",
    "        ax.yaxis.set_major_formatter(plt.NullFormatter())\n",
    "\n",
    "    ax.set_xlabel('$k$')\n",
    "    ax.set_title('$n = %i$' % n)\n",
    "    ax.set_ylim(8E-2, 1E3)\n",
    "    ax.xaxis.set_major_locator(plt.MultipleLocator(n / 5))\n",
    "    ax.grid()\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And note the nice numpy trick `@np.vectorize`, which allows you to magically make a scalar function array-compatible. If you've never seen it, the `@` is a [python decorator](https://realpython.com/primer-on-python-decorators/), which an extremely powerful structure."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "This figure illustrates the behavior of $O_{21}$ as a function of $k$ for two different values of $N$ and for two different values of $b_\\ast$: $b_\\ast = 0.5$  (**M1**: the coin is fair) and $b_\\ast = 0.1$ (**M1**: the coin is biased to tails). \n",
    "\n",
    "*The ability to distinguish  the two hypothesis **improves** with the sample size.*\n",
    "\n",
    "For example:\n",
    "- when $b_\\ast = 0.5$ and $k/N = 0.1$ ($k=1$ on the left and $k=2$ on the right), the odds ratio in favor of **M2** increases from $\\sim 9$ for $N=10$ to $\\sim 263$ for $N=20$. \n",
    "- when k = $b_\\ast N$, the odds ratio is $0.37$ for $N=10$ and 0.27 for $N=20$. \n",
    "- **the simpler model is favored by the data**, and the support strengthens with the sample size. \n",
    "\n",
    "**NOTE** \n",
    "- *$O_{21}= \\sqrt{\\pi/(2N)}$ when k = $b_\\ast N$ and $b_\\ast = 0.5$.* \n",
    "- To build strong evidence that a coin is fair, $O_{21} < 0.1$, it takes as many as $N > 157$ tosses. \n",
    "- With N = 10,000, the heads probability of a fair coin is measured with a precision of 1% and the corresponding odds ratio is $O_{21} \\approx 1/80$.\n",
    "\n",
    "***Frequentist Versus Bayesian***\n",
    "\n",
    "In the **frequentist approach**, we ask whether we can reject the \"null hypothesis\" that our coin is fair. Specifically, we ask whether a given $k$ is a very unusual outcome (at some significance level $\\alpha$, say $\\alpha=0.05$) for a fair coin with $b_\\ast = 0.5$ and with a given N. \n",
    "\n",
    "In the **Bayesian approach**, we offer an alternative hypothesis that the coin has an unknown heads probability. While this probability can be estimated from provided data ($b_0$), **we consider all the possible values** of $b_0$ when comparing the two proposed hypotheses. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Approximate Bayesian Model Comparison <a class=\"anchor\" id=\"three\"></a>\n",
    "\n",
    "While the full *Odds Ratio* is the ultimate goal, it can be costly to compute. So we have some *approximate methods* that balance between ***goodness of fit*** and ***model complexity***. \n",
    "\n",
    "### Akaike information criterion (AIC) \n",
    "\n",
    "We've seen this before! \n",
    "\n",
    "$${\\rm AIC} \\equiv -2 \\ln [L_0(M)] + 2k + \\frac{2k(k+1)}{N-k-1}.$$\n",
    "\n",
    "### Bayesian information criterion (BIC)\n",
    "\n",
    "- The BIC is new to us. \n",
    "- It can be derived from the Bayesian odds ratio by assuming that the likelihood is Gaussian (see $\\S$5.4.2 in textbook for details). \n",
    "- It's easier to compute than the odds ratio because it is based on the maximum value of the likelihood, $L_0(M)$, rather than on the integration of the likelihood over the full parameter space (i.e. evidence $E(M)$). \n",
    "\n",
    "For $N$ data points and a model with $k$ parameters,\n",
    "\n",
    "$${\\rm BIC} \\equiv -2 \\ln [L_0(M)] + k \\ln N.$$ \n",
    "\n",
    "where \n",
    "- the 1st term is equal to the model's $\\chi^2$ (under the assumption of normality; note that this is not $\\chi^2$ per degree of freedom!) and \n",
    "- the 2nd term on the RHS penalizes complex models relative to simple ones.\n",
    "\n",
    "When two models are compared, **the model with the smaller BIC/AIC value wins**. If the models are equally successful in describing the data (i.e., they have the same value of $L_0(M)$), then the model with fewer free parameters wins. \n",
    "\n",
    "Let's use BIC to choose the best polynomial from the earlier line fitting example. \n",
    "Starting with\n",
    "\n",
    "$${\\rm BIC} = \\chi^2 + k \\ln N,$$ \n",
    "\n",
    "with $N=20$ we have:\n",
    "\n",
    "<pre>\n",
    "     model     chi2    k   k*ln(N)   BIC   \n",
    "     ------------------------------------\n",
    "    linear    11.32    2    5.99    17.31   \n",
    "  quadratic    9.46    3    8.99    18.45   \n",
    "     cubic     8.99    4   11.98    20.97  \n",
    "</pre>\n",
    "\n",
    "Therefore, **the improvement in $\\chi^2$ for the quadratic model**, relative to the linear model, **is not large enough to justify another free model parameter.**\n",
    "\n",
    "**BUT NOTE!** \n",
    "- The BIC and AIC are approximations and might not be valid if the underlying assumptions are not met.\n",
    "- Furthermore, unlike the odds ratio, both of them penalize unconstrained parameters. The odds ratio does not care about unconstrained parameters. (Think about this for a second: it's crucial!)\n",
    "- In general, it is better to compute the odds ratio when computationally feasible. "
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