{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "(pymc_overview)=\n", "\n", "# Introductory Overview of PyMC\n", "\n", "Note: This text is partly based on the [PeerJ CS publication on PyMC](https://peerj.com/articles/cs-55/) by John Salvatier, Thomas V. Wiecki, and Christopher Fonnesbeck.\n", "\n", ":::{post} 21 December, 2021\n", ":tags: exploratory analysis, glm, mcmc, pymc.Data, pymc.Deterministic, pymc.DiscreteUniform, pymc.Exponential, pymc.HalfStudentT, pymc.InverseGamma, pymc.HalfNormal, pymc.Model, pymc.Normal, pymc.Poisson, pymc.Slice, pymc.StudentT\n", ":category: beginner\n", ":::" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Abstract\n", "\n", "Probabilistic Programming allows for automatic Bayesian inference on user-defined probabilistic models. Gradient-based algorithms for Markov chain Monte Carlo (MCMC) sampling, known as Hamiltonian Monte Carlo (HMC), allow inference on increasingly complex models but requires gradient information that is often not trivial to calculate. PyMC is an open source probabilistic programming framework written in Python that uses PyTensor to compute gradients via automatic differentiation, as well as compiling probabilistic programs on-the-fly to one of a suite of computational backends for increased speed. PyMC allows for model specification in Python code, rather than in a domain-specific language, making it easy to learn, customize, and debug. This paper is a tutorial-style introduction to this software package for those already somewhat familiar with Bayesian statistics.\n", "\n", "## Introduction\n", "\n", "Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code. PyMC is a PP framework with an intuitive and readable, yet powerful, syntax that is close to the natural syntax statisticians use to describe models. It features next-generation Markov chain Monte Carlo (MCMC) sampling algorithms such as the No-U-Turn Sampler (NUTS; Hoffman, 2014), a self-tuning variant of Hamiltonian Monte Carlo (HMC; Duane, 1987). This class of samplers works well on high-dimensional and complex posterior distributions and allows many complex models to be fit without specialized knowledge about fitting algorithms. HMC and NUTS take advantage of gradient information from the likelihood to achieve much faster convergence than traditional sampling methods, especially for larger models. NUTS also has several self-tuning strategies for adaptively setting the tunable parameters of Hamiltonian Monte Carlo, which means you usually don't need to have specialized knowledge about how the algorithms work. \n", "\n", "Probabilistic programming in Python confers a number of advantages including multi-platform compatibility, an expressive yet clean and readable syntax, easy integration with other scientific libraries, and extensibility via C, C++, Fortran or Cython. These features make it relatively straightforward to write and use custom statistical distributions, samplers and transformation functions, as required by Bayesian analysis.\n", "\n", "While most of PyMC's user-facing features are written in pure Python, it leverages PyTensor (a fork of the Theano project) to transparently transcode models to C and compile them to machine code, thereby boosting performance. PyTensor is a library that allows expressions to be defined using generalized vector data structures called *tensors*, which are tightly integrated with the popular NumPy {class}~numpy.ndarray data structure, and similarly allow for broadcasting and advanced indexing, just as NumPy arrays do. PyTensor also automatically optimizes the likelihood's computational graph for speed and allows for compilation to a suite of computational backends, including Jax and Numba.\n", "\n", "Here, we present a primer on the use of PyMC for solving general Bayesian statistical inference and prediction problems. We will first see the basics of how to use PyMC, motivated by a simple example: installation, data creation, model definition, model fitting and posterior analysis. Then we will cover two case studies and use them to show how to define and fit more sophisticated models. Finally we will discuss a couple of other useful features: custom distributions and arbitrary deterministic nodes." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Installation\n", "\n", "Running PyMC requires a relatively recent Python interpreter, preferably version 3.8 or greater. A complete Python installation for macOS, Linux and Windows can most easily be obtained by downloading and installing the free [Anaconda Python Distribution](https://store.continuum.io/cshop/anaconda/) by ContinuumIO or the open source [Miniforge](https://github.com/conda-forge/miniforge).\n", "\n", "Once Python is installed, follow the {ref}installation guide  on the PyMC documentation site.\n", "\n", "PyMC is distributed under the liberal [Apache License 2.0](https://github.com/pymc-devs/pymc/blob/master/LICENSE). On the GitHub site, users may also report bugs and other issues, as well as contribute documentation or code to the project, which we actively encourage." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A Motivating Example: Linear Regression\n", "\n", "To introduce model definition, fitting, and posterior analysis, we first consider a simple Bayesian linear regression model with normally-distributed priors for the parameters. We are interested in predicting outcomes $Y$ as normally-distributed observations with an expected value $\\mu$ that is a linear function of two predictor variables, $X_1$ and $X_2$:\n", "\n", "\\begin{aligned} \n", "Y &\\sim \\mathcal{N}(\\mu, \\sigma^2) \\\\\n", "\\mu &= \\alpha + \\beta_1 X_1 + \\beta_2 X_2\n", "\\end{aligned}\n", "\n", "where $\\alpha$ is the intercept, and $\\beta_i$ is the coefficient for covariate $X_i$, while $\\sigma$ represents the observation error. Since we are constructing a Bayesian model, we must assign a prior distribution to the unknown variables in the model. We choose zero-mean normal priors with variance of 100 for both regression coefficients, which corresponds to *weak* information regarding the true parameter values. We choose a half-normal distribution (normal distribution bounded at zero) as the prior for $\\sigma$.\n", "\n", "\\begin{aligned} \n", "\\alpha &\\sim \\mathcal{N}(0, 100) \\\\\n", "\\beta_i &\\sim \\mathcal{N}(0, 100) \\\\\n", "\\sigma &\\sim \\lvert\\mathcal{N}(0, 1){\\rvert}\n", "\\end{aligned}\n", "\n", "### Generating data\n", "\n", "We can simulate some artificial data from this model using only NumPy's {mod}~numpy.random module, and then use PyMC to try to recover the corresponding parameters. We are intentionally generating the data to closely correspond the PyMC model structure." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import arviz as az\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%config InlineBackend.figure_format = 'retina'\n", "# Initialize random number generator\n", "RANDOM_SEED = 8927\n", "rng = np.random.default_rng(RANDOM_SEED)\n", "az.style.use(\"arviz-darkgrid\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# True parameter values\n", "alpha, sigma = 1, 1\n", "beta = [1, 2.5]\n", "\n", "# Size of dataset\n", "size = 100\n", "\n", "# Predictor variable\n", "X1 = np.random.randn(size)\n", "X2 = np.random.randn(size) * 0.2\n", "\n", "# Simulate outcome variable\n", "Y = alpha + beta[0] * X1 + beta[1] * X2 + rng.normal(size=size) * sigma" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here is what the simulated data look like. We use the pylab module from the plotting library matplotlib. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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