PyMC Example Gallery

Introductory

General Overview

Introductory Overview of PyMC

Simple Linear Regression

GLM: Linear regression

General API quickstart

General API quickstart

Library Fundamentals

Distribution Dimensionality

Distribution Dimensionality

PyMC and PyTensor

PyMC and PyTensor

Using Data Containers

Using Data Containers

How to

Prior and Posterior Predictive Checks

Prior and Posterior Predictive Checks

Model Comparison

Model comparison

Using a “black box” likelihood function

Using a “black box” likelihood function

Bayesian Missing Data Imputation

Bayesian Missing Data Imputation

Profiling

Profiling

How to wrap a JAX function for use in PyMC

How to wrap a JAX function for use in PyMC

Updating Priors

Updating Priors

Bayesian copula estimation: Describing correlated joint distributions

Bayesian copula estimation: Describing correlated joint distributions

LKJ Cholesky Covariance Priors for Multivariate Normal Models

LKJ Cholesky Covariance Priors for Multivariate Normal Models

Automatic marginalization of discrete variables

Automatic marginalization of discrete variables

Splines

Splines

Using ModelBuilder class for deploying PyMC models

Using ModelBuilder class for deploying PyMC models

How to debug a model

How to debug a model

Generalized Linear Models

Bayesian regression with truncated or censored data

Bayesian regression with truncated or censored data

GLM: Poisson Regression

GLM: Poisson Regression

Regression Models with Ordered Categorical Outcomes

Regression Models with Ordered Categorical Outcomes

Out-Of-Sample Predictions

Out-Of-Sample Predictions

GLM-missing-values-in-covariates

GLM-missing-values-in-covariates

A Primer on Bayesian Methods for Multilevel Modeling

A Primer on Bayesian Methods for Multilevel Modeling

GLM: Robust Linear Regression

GLM: Robust Linear Regression

GLM: Model Selection

GLM: Model Selection

Binomial regression

Binomial regression

GLM-ordinal-features

GLM-ordinal-features

Rolling Regression

Rolling Regression

GLM: Negative Binomial Regression

GLM: Negative Binomial Regression

Hierarchical Binomial Model: Rat Tumor Example

Hierarchical Binomial Model: Rat Tumor Example

Discrete Choice and Random Utility Models

Discrete Choice and Random Utility Models

GLM: Robust Regression using Custom Likelihood for Outlier Classification

GLM: Robust Regression using Custom Likelihood for Outlier Classification

Case Studies

Confirmatory Factor Analysis and Structural Equation Models in Psychometrics

Confirmatory Factor Analysis and Structural Equation Models in Psychometrics

Generalized Extreme Value Distribution

Generalized Extreme Value Distribution

Model building and expansion for golf putting

Model building and expansion for golf putting

NBA Foul Analysis with Item Response Theory

NBA Foul Analysis with Item Response Theory

Forecasting Hurricane Trajectories with State Space Models

Forecasting Hurricane Trajectories with State Space Models

A Hierarchical model for Rugby prediction

A Hierarchical model for Rugby prediction

Reliability Statistics and Predictive Calibration

Reliability Statistics and Predictive Calibration

Factor analysis

Factor analysis

Estimating parameters of a distribution from awkwardly binned data

Estimating parameters of a distribution from awkwardly binned data

Hierarchical Partial Pooling

Hierarchical Partial Pooling

Bayesian Estimation Supersedes the T-Test

Bayesian Estimation Supersedes the T-Test

Fitting a Reinforcement Learning Model to Behavioral Data with PyMC

Fitting a Reinforcement Learning Model to Behavioral Data with PyMC

Probabilistic Matrix Factorization for Making Personalized Recommendations

Probabilistic Matrix Factorization for Making Personalized Recommendations

Causal Inference

Interrupted time series analysis

Interrupted time series analysis

Difference in differences

Difference in differences

Interventional distributions and graph mutation with the do-operator

Interventional distributions and graph mutation with the do-operator

Bayesian moderation analysis

Bayesian moderation analysis

Introduction to Bayesian A/B Testing

Introduction to Bayesian A/B Testing

Simpson’s paradox

Simpson’s paradox

Regression discontinuity design analysis

Regression discontinuity design analysis

Bayesian Non-parametric Causal Inference

Bayesian Non-parametric Causal Inference

Bayesian mediation analysis

Bayesian mediation analysis

Counterfactual inference: calculating excess deaths due to COVID-19

Counterfactual inference: calculating excess deaths due to COVID-19

Gaussian Processes

Kronecker Structured Covariances

Kronecker Structured Covariances

Modeling spatial point patterns with a marked log-Gaussian Cox process

Modeling spatial point patterns with a marked log-Gaussian Cox process

Gaussian Process for CO2 at Mauna Loa

Gaussian Process for CO2 at Mauna Loa

Multi-output Gaussian Processes: Coregionalization models using Hamadard product

Multi-output Gaussian Processes: Coregionalization models using Hamadard product

Gaussian Processes: Latent Variable Implementation

Gaussian Processes: Latent Variable Implementation

Gaussian Processes: HSGP Reference & First Steps

Gaussian Processes: HSGP Reference & First Steps

Gaussian Processes: HSGP Advanced Usage

Gaussian Processes: HSGP Advanced Usage

Gaussian Processes using numpy kernel

Gaussian Processes using numpy kernel

Heteroskedastic Gaussian Processes

Heteroskedastic Gaussian Processes

Baby Births Modelling with HSGPs

Baby Births Modelling with HSGPs

GP-Circular

GP-Circular

Example: Mauna Loa CO_2 continued

Example: Mauna Loa CO_2 continued

Gaussian Process (GP) smoothing

Gaussian Process (GP) smoothing

Mean and Covariance Functions

Mean and Covariance Functions

Sparse Approximations

Sparse Approximations

Marginal Likelihood Implementation

Marginal Likelihood Implementation

Student-t Process

Student-t Process

Time Series

Stochastic Volatility model

Stochastic Volatility model

Analysis of An AR(1) Model in PyMC

Analysis of An AR(1) Model in PyMC

Time Series Models Derived From a Generative Graph

Time Series Models Derived From a Generative Graph

Multivariate Gaussian Random Walk

Multivariate Gaussian Random Walk

Bayesian Vector Autoregressive Models

Bayesian Vector Autoregressive Models

Air passengers - Prophet-like model

Air passengers - Prophet-like model

Inferring parameters of SDEs using a Euler-Maruyama scheme

Inferring parameters of SDEs using a Euler-Maruyama scheme

Longitudinal Models of Change

Longitudinal Models of Change

Forecasting with Structural AR Timeseries

Forecasting with Structural AR Timeseries

Spatial Analysis

Conditional Autoregressive (CAR) Models for Spatial Data

Conditional Autoregressive (CAR) Models for Spatial Data

The prevalence of malaria in the Gambia

The prevalence of malaria in the Gambia

The Besag-York-Mollie Model for Spatial Data

The Besag-York-Mollie Model for Spatial Data

Diagnostics and Model Criticism

Diagnosing Biased Inference with Divergences

Diagnosing Biased Inference with Divergences

Model Averaging

Model Averaging

Sampler Statistics

Sampler Statistics

Bayes Factors and Marginal Likelihood

Bayes Factors and Marginal Likelihood

Bayesian Additive Regression Trees

Bayesian Additive Regression Trees: Introduction

Bayesian Additive Regression Trees: Introduction

Categorical regression

Categorical regression

Quantile Regression with BART

Quantile Regression with BART

Modeling Heteroscedasticity with BART

Modeling Heteroscedasticity with BART

Mixture Models

Dependent density regression

Dependent density regression

Dirichlet mixtures of multinomials

Dirichlet mixtures of multinomials

Dirichlet process mixtures for density estimation

Dirichlet process mixtures for density estimation

Marginalized Gaussian Mixture Model

Marginalized Gaussian Mixture Model

Gaussian Mixture Model

Gaussian Mixture Model

Survival Analysis

Bayesian Survival Analysis

Bayesian Survival Analysis

Frailty and Survival Regression Models

Frailty and Survival Regression Models

Censored Data Models

Censored Data Models

Bayesian Parametric Survival Analysis

Bayesian Parametric Survival Analysis

Reparameterizing the Weibull Accelerated Failure Time Model

Reparameterizing the Weibull Accelerated Failure Time Model

ODE models

pymc3.ode: Shapes and benchmarking

pymc3.ode: Shapes and benchmarking

Lotka-Volterra with manual gradients

Lotka-Volterra with manual gradients

GSoC 2019: Introduction of pymc3.ode API

GSoC 2019: Introduction of pymc3.ode API

ODE Lotka-Volterra With Bayesian Inference in Multiple Ways

ODE Lotka-Volterra With Bayesian Inference in Multiple Ways

MCMC

Sequential Monte Carlo

Sequential Monte Carlo

DEMetropolis and DEMetropolis(Z) Algorithm Comparisons

DEMetropolis and DEMetropolis(Z) Algorithm Comparisons

Approximate Bayesian Computation

Approximate Bayesian Computation

Faster Sampling with JAX and Numba

Faster Sampling with JAX and Numba

Using a custom step method for sampling from locally conjugate posterior distributions

Using a custom step method for sampling from locally conjugate posterior distributions

Compound Steps in Sampling

Compound Steps in Sampling

DEMetropolis(Z) Sampler Tuning

DEMetropolis(Z) Sampler Tuning

Lasso regression with block updating

Lasso regression with block updating

Variational Inference

Empirical Approximation overview

Empirical Approximation overview

Pathfinder Variational Inference

Pathfinder Variational Inference

Introduction to Variational Inference with PyMC

Introduction to Variational Inference with PyMC

GLM: Mini-batch ADVI on hierarchical regression model

GLM: Mini-batch ADVI on hierarchical regression model

Variational Inference: Bayesian Neural Networks

Variational Inference: Bayesian Neural Networks