diff --git a/04_probability_distributions.ipynb b/04_probability_distributions.ipynb index 1c50268..8a3791b 100644 --- a/04_probability_distributions.ipynb +++ b/04_probability_distributions.ipynb @@ -1413,7 +1413,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Measuring distances btween distributions\n", + "## Measuring distances between distributions\n", "\n", "There are several ways to measure distances between two probability distributions with PDFs $p(x)$ and $q(x)$, each with its own characteristics and applications. \n", "\n", diff --git a/05_Bayesian_inference.ipynb b/05_Bayesian_inference.ipynb index 649f332..2cd9cdd 100644 --- a/05_Bayesian_inference.ipynb +++ b/05_Bayesian_inference.ipynb @@ -244,9 +244,9 @@ "\n", "What does it take?\n", "\n", - "- `Data`\n", - "- A generative model (how does the conditional `likelihood` come about?)\n", - "- Our `beliefs` before seeing the data.\n", + "- Data,\n", + "- A generative model,\n", + "- Our beliefs before seeing the data.\n", "\n", "What does it make?\n", "\n", diff --git a/09_intro_to_Numpyro.ipynb b/09_intro_to_Numpyro.ipynb index 0b1c907..1735f97 100644 --- a/09_intro_to_Numpyro.ipynb +++ b/09_intro_to_Numpyro.ipynb @@ -352,7 +352,7 @@ "`````{admonition} Task: Point estimates for Bernoulli-beta coin flips\n", ":class: tip\n", "- You might have correctly noticed that we have not looked at the `Predictive` capability. Study the documentation of Numpyro (in particular, `numpyro.infer`) and demonstrate the `Predictive` command on the example shown above.\n", - "- Study the documentation of Numpyro (in particular, `numpyro.diagnostics`) to undertand what the `hpdi` command does. Apply it to the example shown above.\n", + "- Study the documentation of Numpyro (in particular, `numpyro.diagnostics`) to understand what the `hpdi` command does. Apply it to the example shown above.\n", "`````" ] }, diff --git a/11_Bayesian_workflow.ipynb b/11_Bayesian_workflow.ipynb new file mode 100644 index 0000000..e72a3be --- /dev/null +++ b/11_Bayesian_workflow.ipynb @@ -0,0 +1,1211 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "J1LV5w4eFSzA" + }, + "source": [ + "# Bayesian workflow\n", + "\n", + "Leveraging Bayesian inference for addressing real-world problems requires from the modeller not only to be proficient in statsitics, have domain expertise and programming skills, but also a deep understanding of the decision-making process while analysing data. Apart from inference, the workflow includes iterative model building, model checking, validation and troubleshooting of computational problems, model understanding, and model comparison.\n", + "\n", + "Seemingly, the Bayes rule looks very simple:\n", + "\n", + "$$\\underbrace{p(\\theta|y)}_\\text{posterior} \\propto \\underbrace{p(y | \\theta)}_{\\text{likelihood}} \\underbrace{p(\\theta)}_{\\text{prior}}$$\n", + "\n", + "What could possibly go wrong about it in practice?\n", + "\n", + "A lot can go wrong! And in case things go wrong, decisions need to be made sequentially about model building and improvement. That is why we need the Bayesian workflow." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Principles of Bayesian workflow\n", + "\n", + "Workflows exist in a variety of disciplines where they define what is a 'good practice'.\n", + "\n", + "\n", + "## Box's loop\n", + "\n", + "In the 1960's, the statistician Box formulated the notion of a loop to understand the nature of the scientific method. This loop is called Box's loop by Blei et. al. (2014):\n", + "\n", + "\n", + "![](assets/boxes_loop.png)\n", + "\n", + "\n", + "## Modern Bayesian workflow\n", + "\n", + "A systematic review of the steps within the modern Bayesian workflow, described in Gelman et al. (2020):\n", + "\n", + "![](assets/bayes_workflow.png)\n", + "\n", + "## Prior predictive checks\n", + "\n", + "Prior predictive checking consists in simulating data from the priors. Then such simulations are commonly visualized (especially when transformations of parameters is involved). This shows the range of data compatible with the model, helps understand the adequacy of the chosen priors, as it is often easier to elicit expert knowledge on measureable quantities of interest rather than abstract parameter values.\n", + "\n", + "\n", + "## Iterative model building\n", + "\n", + "A possible realisation of the Bayeisan workflow loop:\n", + "\n", + "- Understand the domain and problem,\n", + "\n", + "- Formulate the model mathematically,\n", + "\n", + "- Implement model, test, debug,\n", + "\n", + "- debug, debug, debug.\n", + "\n", + "- Perform prior predictive, check,\n", + "\n", + "- Fit the model,\n", + "\n", + "- Assess convergence diagnostics,\n", + "\n", + "- Perform posterior predictive check, \n", + "\n", + "- Improve the model iteratively: from baseline to complex and computationally efficient models.\n", + "\n", + "## Examples\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/anaconda3/envs/aims/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import MCMC, NUTS, Predictive\n", + "from numpyro.diagnostics import hpdi\n", + "\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from jax import random\n", + "\n", + "import arviz as az\n", + "from scipy.stats import gaussian_kde\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Coin tossing " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "n = 100 # number of trials\n", + "h = 61 # number of successes\n", + "alpha = 2 # hyperparameters\n", + "beta = 2\n", + "\n", + "niter = 1000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```{margin}\n", + "Note `h=None` here. If we pass data for `h`, inference will be performed by conditioning on this data. Otherwise we will obtain prior predictive samples.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def model(n, alpha=2, beta=2, h=None):\n", + "\n", + " # prior on the probability of success p\n", + " p = numpyro.sample('p', dist.Beta(alpha, beta))\n", + "\n", + " # likelihood - notice the `obs=h` part\n", + " # p is the probabiity of success,\n", + " # n is the total number of experiments\n", + " # h is the number of successes\n", + " numpyro.sample('obs', dist.Binomial(n, p), obs=h)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Prior Predictive check" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "rng_key = random.PRNGKey(0)\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "\n", + "# use the Predictive class to generate predictions.\n", + "# Notice that we are not passing observation `h` as data.\n", + "# Since we have set `h=None`, this allows the model to make predictions of `h`\n", + "# when data for it is not provided.\n", + "prior_predictive = Predictive(model, num_samples=1000)\n", + "prior_predictions = prior_predictive(rng_key_, n)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['obs', 'p'])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# we have generated samples for two variables\n", + "prior_predictions.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# extract samples for variable 'p'\n", + "pred_obs = prior_predictions['p']\n", + "\n", + "# compute its summary statistics for the samples of `p`\n", + "mean_prior_pred = jnp.mean(pred_obs, axis=0)\n", + "hpdi_prior_pred = hpdi(pred_obs, 0.89)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=100, figsize=(5, 3))\n", + "plt.hist(pred_obs, bins=15, density=True, alpha=0.5, color='teal')\n", + "x = jnp.linspace(0, 1, 3000)\n", + "kde = gaussian_kde(pred_obs)\n", + "plt.plot(x, kde(x), color='teal', lw=3, alpha=0.5)\n", + "plt.xlabel('p')\n", + "plt.title('Prior predictive distribution for $p$')\n", + "plt.xlim(0, 1)\n", + "plt.grid(0.3)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Inference\n", + "\n", + "Using the same routine as we did for prior redictive, we can perform inference by using the observed data." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":8: UserWarning: There are not enough devices to run parallel chains: expected 4 but got 1. Chains will be drawn sequentially. If you are running MCMC in CPU, consider using `numpyro.set_host_device_count(4)` at the beginning of your program. You can double-check how many devices are available in your system using `jax.local_device_count()`.\n", + " mcmc = MCMC(kernel, num_warmup=1000, num_samples=2000, num_chains=4, progress_bar=False)\n" + ] + } + ], + "source": [ + "rng_key = random.PRNGKey(0)\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "\n", + "# specify inference algorithm\n", + "kernel = NUTS(model)\n", + "\n", + "# define number of samples and number chains\n", + "mcmc = MCMC(kernel, num_warmup=1000, num_samples=2000, num_chains=4, progress_bar=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "#run MCMC\n", + "mcmc.run(rng_key_, n=n, h=h)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# exatract samples of parameter p\n", + "p_samples = mcmc.get_samples()\n", + "p_posterior_samples = p_samples['p']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(dpi=100, figsize=(5, 3))\n", + "plt.hist(pred_obs, bins=15, density=True, alpha=0.5, color='teal', label = \"Prior distribution\")\n", + "plt.hist(p_posterior_samples, bins=15, density=True, alpha=0.5, color='orangered', label = \"Posterior distribution\")\n", + "x = jnp.linspace(0, 1, 3000)\n", + "kde = gaussian_kde(pred_obs)\n", + "plt.plot(x, kde(x), color='teal', lw=3, alpha=0.5)\n", + "kde = gaussian_kde(p_posterior_samples)\n", + "plt.plot(x, kde(x), color='orangered', lw=3, alpha=0.5)\n", + "plt.xlabel('p')\n", + "plt.xlim(0, 1)\n", + "plt.grid(0.3)\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Check convergence\n", + "\n", + "We now have obtained the samples from MCMC. How can we assess whether we can trust the results? Convergence diganostics survey this purpose. Beyond $\\hat{R}$, we can also visually inspect traceplots. Traceplots are simply sample values plotted against the iteration number. We want those traceplots to be stationary, i.e. they should look like a \"hairy carterpillar\"." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " mean std median 5.0% 95.0% n_eff r_hat\n", + " p 0.61 0.05 0.61 0.53 0.68 3059.08 1.00\n", + "\n", + "Number of divergences: 0\n" + ] + } + ], + "source": [ + "# inpect summary\n", + "# pring summary and look at R-hat\n", + "# r_hat is a dignostic comparing within chain variation to between chan variation.\n", + "# It is an importnat convergene diagnostic, and we want its valye to be close to 1\n", + "mcmc.print_summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot posterior distribution and traceplots\n", + "data = az.from_numpyro(mcmc)\n", + "az.plot_trace(data, compact=True);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Posterior predictive distribution\n", + "\n", + "The posterior predictive distribution is a concept in Bayesian statistics that combines the information from both the observed data and the posterior distribution of model parameters to generate predictions for new, unseen data .\n", + "\n", + "We can use the obtained samples obtained at the previous step to generate posterior predictive desitribution on the outcome." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "# using the same 'Predictive' class,\n", + "# but now specifying also `p_samples`\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "predictive = Predictive(model, p_samples)\n", + "posterior_predictions = predictive(rng_key_, n=n)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# extract prediction and calculate summary statistics\n", + "post_obs = posterior_predictions['obs']\n", + "mean_post_pred = jnp.mean(post_obs, axis=0)\n", + "hpdi_post_pred = hpdi(post_obs, 0.9)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(60.508003, dtype=float32)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# what is the mean number of successes?\n", + "mean_post_pred" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([48, 70], dtype=int32)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# what is the unceratinty around this mean?\n", + "hpdi_post_pred" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Group task:** change the hyperparamaters of the model. How are they changing the results?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bayesian Linear regression\n", + "\n", + "Now that we know how to use NumPyro. Let us build an example using larger amounts of data and build a Bayesian Linear Regression model. It is the same Linear Regression model you are familiar with, but here all of the parameters are estimated in the Bayesian way." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--2024-03-19 22:17:00-- https://raw.githubusercontent.com/deep-learning-indaba/indaba-pracs-2023/main/data/Howell1.csv\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 12205 (12K) [text/plain]\n", + "Saving to: ‘Howell1.csv’\n", + "\n", + "Howell1.csv 100%[===================>] 11.92K --.-KB/s in 0.002s \n", + "\n", + "2024-03-19 22:17:00 (5.75 MB/s) - ‘Howell1.csv’ saved [12205/12205]\n", + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
heightweightagemale
0151.76547.82560663.01
1139.70036.48580763.00
2136.52531.86483865.00
3156.84553.04191441.01
4145.41541.27687251.00
\n", + "
" + ], + "text/plain": [ + " height weight age male\n", + "0 151.765 47.825606 63.0 1\n", + "1 139.700 36.485807 63.0 0\n", + "2 136.525 31.864838 65.0 0\n", + "3 156.845 53.041914 41.0 1\n", + "4 145.415 41.276872 51.0 0" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "!wget -O Howell1.csv https://raw.githubusercontent.com/deep-learning-indaba/indaba-pracs-2023/main/data/Howell1.csv\n", + "\n", + "df = pd.read_csv('Howell1.csv', sep=\";\")\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# observed data\n", + "weight = df.weight.values\n", + "height = df.height.values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us define some test data for the variable `weight`. For these datapoints we will make predictions." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "# data to make predictions for\n", + "weight_pred = jnp.array([45, 40, 65, 31, 53])" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot the data\n", + "plt.figure(figsize=(6, 4))\n", + "plt.scatter(x='weight', y='height', data=df, color='teal')\n", + "plt.grid(0.3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The linear regression model will have the form\n", + "\n", + "$$y \\sim N(\\mu, \\sigma^2),\\\\\n", + "\\mu = b_0 + b_1 x.$$\n", + "\n", + "Here $y$ is the data we want to predict, $x$ is the predictor, $b_0$ is the bias (intercept), $b_1$ is the slope (weight) and $\\sigma^2$ is variance.\n", + "\n", + "**Group task:** Discuss which priors would be reasonable for the parameters $b_0$, $b_1$, $\\sigma$." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# model\n", + "def model(weight=None, height=None):\n", + " # priors\n", + " b0 = numpyro.sample('b0', dist.Normal(120,50))\n", + " b1 = numpyro.sample('b1', dist.Normal(0,1))\n", + " sigma = numpyro.sample('sigma', dist.HalfNormal(10.))\n", + "\n", + " # deterministic transformation\n", + " mu = b0 + b1 * weight\n", + "\n", + " # likelihood: notice `obs=height`\n", + " numpyro.sample('obs', dist.Normal(mu, sigma), obs=height)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "# prior predictive\n", + "rng_key = random.PRNGKey(0)\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "prior_predictive = Predictive(model, num_samples=100)\n", + "prior_predictions = prior_predictive(rng_key_, weight)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['b0', 'b1', 'obs', 'sigma'])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "prior_predictions.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "pred_obs = prior_predictions['obs']\n", + "mean_prior_pred = jnp.mean(pred_obs, axis=0)\n", + "hpdi_prior_pred = hpdi(pred_obs, 0.89)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_regression(x, y_mean, y_hpdi, height, ttl='Predictions with 89% CI)'):\n", + " # Sort values for plotting by x axis\n", + " idx = jnp.argsort(x)\n", + " weight = x[idx]\n", + " mean = y_mean[idx]\n", + " hpdi = y_hpdi[:, idx]\n", + " ht = height[idx]\n", + "\n", + " # Plot\n", + " fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 6))\n", + " ax.plot(weight, mean, color='teal')\n", + " ax.plot(weight, ht, 'o', color='orangered')\n", + " ax.fill_between(weight, hpdi[0], hpdi[1], alpha=0.3, interpolate=True, color='teal')\n", + " ax.set(xlabel='weight', ylabel='height', title=ttl);\n", + " return ax" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ax = plot_regression(weight, mean_prior_pred, hpdi_prior_pred, height, ttl=\"Prior predictive\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":7: UserWarning: There are not enough devices to run parallel chains: expected 4 but got 1. Chains will be drawn sequentially. If you are running MCMC in CPU, consider using `numpyro.set_host_device_count(4)` at the beginning of your program. You can double-check how many devices are available in your system using `jax.local_device_count()`.\n", + " mcmc = MCMC(kernel, num_warmup=1000, num_samples=2000, num_chains=4, progress_bar=False)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " mean std median 5.0% 95.0% n_eff r_hat\n", + " b0 75.49 1.07 75.48 73.72 77.26 2608.93 1.00\n", + " b1 1.76 0.03 1.76 1.72 1.81 2692.35 1.00\n", + " sigma 9.37 0.29 9.36 8.86 9.82 3778.49 1.00\n", + "\n", + "Number of divergences: 0\n" + ] + } + ], + "source": [ + "# Inference\n", + "rng_key = random.PRNGKey(0)\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "\n", + "# Run NUTS\n", + "kernel = NUTS(model)\n", + "mcmc = MCMC(kernel, num_warmup=1000, num_samples=2000, num_chains=4, progress_bar=False)\n", + "mcmc.run(rng_key_, weight=weight, height=height)\n", + "mcmc.print_summary()\n", + "samples_1 = mcmc.get_samples()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " mean std median 5.0% 95.0% n_eff r_hat\n", + " b0 75.49 1.07 75.48 73.72 77.26 2608.93 1.00\n", + " b1 1.76 0.03 1.76 1.72 1.81 2692.35 1.00\n", + " sigma 9.37 0.29 9.36 8.86 9.82 3778.49 1.00\n", + "\n", + "Number of divergences: 0\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Check convergence\n", + "mcmc.print_summary()\n", + "data = az.from_numpyro(mcmc)\n", + "az.plot_trace(data, compact=True);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Posterior predictive\n", + "rng_key, rng_key_ = random.split(rng_key)\n", + "predictive = Predictive(model, samples_1)\n", + "posterior_predictions = predictive(rng_key_, weight=weight)\n", + "post_obs = posterior_predictions['obs']\n", + "\n", + "mean_post_pred = jnp.mean(post_obs, axis=0)\n", + "hpdi_post_pred = hpdi(post_obs, 0.9)\n", + "\n", + "ax = plot_regression(weight, mean_post_pred, hpdi_post_pred, height, ttl=\"Posterior predictive\")\n", + "ax.set(xlabel='weight (scaled)', ylabel='height (scaled)');" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
weight_predmean_predlowerupper
045154.772690139.393387169.614548
140146.176010131.200302161.135223
265190.045502175.474350204.991074
331130.221954115.344894145.279709
453168.721436154.352890184.339874
\n", + "
" + ], + "text/plain": [ + " weight_pred mean_pred lower upper\n", + "0 45 154.772690 139.393387 169.614548\n", + "1 40 146.176010 131.200302 161.135223\n", + "2 65 190.045502 175.474350 204.991074\n", + "3 31 130.221954 115.344894 145.279709\n", + "4 53 168.721436 154.352890 184.339874" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# predict for new data\n", + "predictive = Predictive(model, samples_1)\n", + "predictions = predictive(rng_key_, weight=weight_pred)['obs']\n", + "\n", + "mean_pred = jnp.mean(predictions, axis=0)\n", + "hpdi_pred = hpdi(predictions, 0.89)\n", + "\n", + "d = {'weight_pred': weight_pred, 'mean_pred': mean_pred, 'lower': hpdi_pred[0,], 'upper': hpdi_pred[1,]}\n", + "df_res = pd.DataFrame(data=d)\n", + "df_res.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`````{admonition} Task\n", + ":class: tip\n", + "Modify the model so that it fits better. \n", + "\n", + "**Hint:** apply a transformation to input data, e.g. a polynomial.\n", + "\n", + "For this model, \n", + "\n", + "- plot prior predictive distribution,\n", + "- perform inference,\n", + "- plot posterior predictive dsitribution.\n", + "`````\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model comparison\n", + "\n", + "It often occurrs in practice that we have several model candidates at hand and need to choose the best model for the given data.\n", + "\n", + "It is a tricky task, since increasing model complexity typically leads to improved data fitting by introducing more parameters, creating the the risk of overfitting.\n", + "\n", + "Hence, the models we are looking for, should not just describe well the observed data, but, ideally, the entire \"true\" data generating process. We need to find tools to quantify the degree of “closeness” to the true model. Note that in this context models refer to the distributional family as well as the parameter values.\n", + "\n", + "We could use KLD to measure the degree of “closeness” between two models $M_0$ and $M_1$:\n", + "\n", + "$$\n", + "\\text{KLD}(M_0 \\parallel M_1) = \\int p_{M_0}(y) \\log \\left( \\frac{p_{M_0}(y)}{p_{M_1}(y)} \\right) dy = \\int p_{M_0}(y) \\log p_{M_0}(y) dy - \\int p_{M_0}(y) \\log p_{M_1}(y) dy\n", + "$$\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`````{admonition} Task \n", + ":class: tip\n", + "\n", + "Assume that the 'true' model $M_0$ and the two candidate modelas are $M_1$ and $M_2$\n", + "\n", + "- $M_0: y \\sim \\mathcal{N}(3,2)$\n", + "- $M_1: y \\sim \\mathcal{N}(3.5,2.5)$\n", + "- $M_2: y \\sim \\text{Cauchy}(3,2)$\n", + "\n", + "For these models,\n", + "\n", + "- Compute divergences $\\text{KLD}(M_0 \\parallel M_1)$, $\\text{KLD}(M_0 \\parallel M_2)$\n", + "- Which model is better: $M_1$ or $M_2$?\n", + "\n", + "`````" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that the first term in $\\text{KLD}(M_0 \\parallel M_1)$ is always the same. Hence, we only need to compare models on the second term $\\int p_{M_0}(y) \\log p_{M_1}(y) dy$, which is the expected log predictive density (elpd):\n", + "\n", + " $$\n", + " \\int p_{M_0}(y) \\log p_{M_1}(y) dy = \\mathbb{E}[ \\log p_{M_1}].\n", + " $$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The problem we have here is taht in reality we never know the true model $M_0.$ Several numerical metrics are commonly used for this purpose in the literature such as infromation criteria and cross validation.\n", + "\n", + "### Informtation criteria\n", + "\n", + "Akaike Information Criterion (AIC)\n", + " \n", + "$$\n", + "\\text{AIC} = - 2 l(\\hat{\\theta}_\\text{MLE}) + 2p,\n", + "$$\n", + "\n", + "where $l$ is the log-likelihood, $p$ is the number of parameters and $\\theta_\\text{MLE}$ is the MLE estimate.\n", + "\n", + "A lower AIC value indicates a better trade-off between model fit and complexity, implying a better model.\n", + "\n", + "AIC works best when the probability distribution under $M_1$ is normal, and the sample size is much larger than the number of parameters. No posterior distribution is used, as $D$ is computed only based on the MLE. It does not take into account any prior information.\n", + "\n", + "Bayesian Information Criterion (AIC)\n", + "\n", + "$$\n", + "\\text{BIC} = - 2 l(\\hat{\\theta}_\\text{MLE}) + p \\ln(n),\n", + "$$\n", + "\n", + "where $n$ is the number of datapoints.\n", + "\n", + "BIC is derived using the Laplace approximation. It is only valid for sample size $n$ much larger than the number $p$ of parameters in the model. The BIC is independent of the prior and generally penalizes free parameters more strongly than the Akaike information criterion, though it depends on the size of $n$ and relative magnitude of $n$ and $k$.\n", + "\n", + "Watanabe-Akaike Information Criteria (WAIC)\n", + "\n", + "$$\n", + "\\begin{align*}\n", + "\\text{WAIC} = &- 2 \\sum_{i=1}^{n} \\log \\mathbb{E}[p(y_i | \\theta, y)] + 2p_\\text{WAIC} \\\\\n", + " &-2 \\left( \\sum_{i=1}^{n} \\log \\left( \\frac{1}{S} \\sum_{s=1}^{S} p(y_i|\\theta_s) \\right) - \\sum_{i=1}^{n} \\text{Var}_s \\left( \\log p(y_i|\\theta_s) \\right) \\right)\n", + "\\end{align*}\n", + "$$\n", + "\n", + "where $ \\mathbb{E}[p(y_i | \\theta, y)]$ is the posterior mean of the likelihood of the $i$-th observation, $n$ is the number of data points, $S$ is the number of posterior samples.\n", + "\n", + "The WAIC incorporates prior information, and the use of pointwise likelihood makes it more robust when the posterior distributions deviate from normality." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leave-One-Out Cross Validation\n", + "\n", + "Cross validation splits the current sample into $k$ parts. Then a model is being fit on $k−1$ parts and the predictions are make for the remaiining $1$ part.\n", + "\n", + "A special case is when $k=N$ so that each time one uses $N- 1$ data points to estimate the model parameters, and estimate the elpd for the observation that was left out. This is called leave-one-out cross-validation (LOO-CV). See [Vehrari, Gelman, Gabry (2016)](https://arxiv.org/pdf/1507.04544.pdf) for the details of how LOO elpd can be estomated from samples.\n", + "\n", + "\n", + "We can use tools from `arviz` library to help us [perform model comparison](https://python.arviz.org/en/latest/examples/plot_compare.html)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`````{admonition} Task \n", + ":class: tip\n", + "\n", + "Download the `kidiq` dataset (Gelman & Hill, 2007), which is data from a survey of adult American women and their respective children. Dated from 2007, it has 434 observations and 4 variables:\n", + "\n", + "- `kid_score`: child's IQ\n", + "\n", + "- `mom_hs`: binary/dummy (0 or 1) if the child's mother has a high school diploma\n", + "\n", + "- `mom_iq`: mother's IQ\n", + "\n", + "- `mom_age`: mother's age\n", + "\n", + "with \n", + "\n", + "```\n", + "import pandas as pd\n", + "\n", + "!wget -O kidiq.csv https://github.com/TuringLang/TuringGLM.jl/raw/main/data/kidiq.csv\n", + "\n", + "df = pd.read_csv('kidiq.csv')\n", + "```\n", + "\n", + "Construct a model predicting model predicting `kid_score`:\n", + "\n", + "$$\n", + "\\text{kidscore}_i \\sim \\mathcal{N}(\\mu_i, \\sigma),\n", + "$$\n", + "\n", + "- Construct several model of $\\mu_i$ using the available predictors. \n", + "\n", + "- What models have you tried and which models performed the best?\n", + "\n", + "`````\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.18" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/999_acknowledgements.md b/999_acknowledgements.md index 270127e..0bbe0ca 100644 --- a/999_acknowledgements.md +++ b/999_acknowledgements.md @@ -3,6 +3,7 @@ ## Acknowledgements and links - AIMS and Ulrich personally for the invitation - [Machine Learning and Global Health](mlgh.net/people) network for many things, but in particular for the (virtual, at the time) space where I learnt Numpyro through a reading group together with some MLGH members: Swapnil Mishra, Iwona Hawryluk, Tim Wolock, Theo Rashid, Giovanni Charles +- [Deep Learning Indaba](https://deeplearningindaba.com/) for showing me how much ML enthisuams there is on the African continent and making me want to contribute - Co-authors of the paper [Bayesian workflow for disease transmission modeling in Stan](https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.9164) and all particiapnts of the regular Thursday Stan call which enabled me to co-author - Lorenzo Ciardo from Kellogg College at Oxford for telling me about the Buffon's needle problem - Richard McEarlth for posting the [prior-likelihood conflict example](https://twitter.com/rlmcelreath/status/1701165075493470644) diff --git a/_toc.yml b/_toc.yml index 64e8041..a0d7441 100644 --- a/_toc.yml +++ b/_toc.yml @@ -13,4 +13,5 @@ chapters: - file: 08_PPLs.ipynb - file: 09_intro_to_Numpyro.ipynb - file: 10_focus_on_priors.ipynb +- file: 11_Bayesian_workflow.ipynb - file: 999_acknowledgements.md \ No newline at end of file diff --git a/assets/bayes_workflow.png b/assets/bayes_workflow.png new file mode 100644 index 0000000..342585a Binary files /dev/null and b/assets/bayes_workflow.png differ diff --git a/assets/boxes_loop.png b/assets/boxes_loop.png new file mode 100644 index 0000000..a47e9d6 Binary files /dev/null and b/assets/boxes_loop.png differ