PyMC Example Gallery# Core notebooks# Introductory Overview of PyMC GLM: Linear regression Model Comparison Prior and Posterior Predictive Checks Distribution Dimensionality PyMC and Aesara (Generalized) Linear and Hierarchical Linear Models# Bayesian regression with truncated or censored data Simpson’s paradox and mixed models Rolling Regression GLM: Robust Regression using Custom Likelihood for Outlier Classification GLM: Robust Linear Regression GLM: Poisson Regression Out-Of-Sample Predictions GLM: Negative Binomial Regression GLM: Model Selection Hierarchical Binomial Model: Rat Tumor Example Binomial regression Case Studies# How to wrap a JAX function for use in PyMC Stochastic Volatility model Splines A Hierarchical model for Rugby prediction Reliability Statistics and Predictive Calibration Fitting a Reinforcement Learning Model to Behavioral Data with PyMC Model building and expansion for golf putting Probabilistic Matrix Factorization for Making Personalized Recommendations A Primer on Bayesian Methods for Multilevel Modeling Bayesian moderation analysis Bayesian mediation analysis NBA Foul Analysis with Item Response Theory Hierarchical Partial Pooling Factor analysis Conditional Autoregressive (CAR) model Using a “black box” likelihood function (numpy) Using a “black box” likelihood function (Cython) Estimating parameters of a distribution from awkwardly binned data Introduction to Bayesian A/B Testing LKJ Cholesky Covariance Priors for Multivariate Normal Models Generalized Extreme Value Distribution Bayesian Estimation Supersedes the T-Test Bayesian Additive Regression Trees: Introduction Causal Inference# Regression discontinuity design analysis Interrupted time series analysis Counterfactual inference: calculating excess deaths due to COVID-19 Difference in differences Diagnostics and Model Criticism# Sampler Statistics Model Averaging Diagnosing Biased Inference with Divergences Bayes Factors and Marginal Likelihood Gaussian Processes# Modeling spatial point patterns with a marked log-Gaussian Cox process Gaussian Processes using numpy kernel Multi-output Gaussian Processes: Coregionalization models using Hamadard product Gaussian Process (GP) smoothing Student-t Process Sparse Approximations Mean and Covariance Functions Example: Mauna Loa CO_2 continued Gaussian Process for CO2 at Mauna Loa Marginal Likelihood Implementation Gaussian Processes: Latent Variable Implementation Kronecker Structured Covariances Heteroskedastic Gaussian Processes GP-Circular Inference in ODE models# Lotka-Volterra with manual gradients pymc3.ode: Shapes and benchmarking GSoC 2019: Introduction of pymc3.ode API MCMC# Sequential Monte Carlo Approximate Bayesian Computation Variance reduction in MLDA - Linear regression The MLDA sampler MLDA sampler: Introduction and resources Multilevel Gravity Survey with MLDA Using JAX for faster sampling DEMetropolis(Z): tune_drop_fraction DEMetropolis(Z): Population vs. History efficiency comparison Mixture Models# Marginalized Gaussian Mixture Model Gaussian Mixture Model Dirichlet process mixtures for density estimation Dirichlet mixtures of multinomials Dependent density regression Survival Analysis# Reparameterizing the Weibull Accelerated Failure Time Model Bayesian Survival Analysis Censored Data Models Bayesian Parametric Survival Analysis with PyMC3 Time Series# Bayesian Vector Autoregressive Models Multivariate Gaussian Random Walk Forecasting with Structural AR Timeseries Inferring parameters of SDEs using a Euler-Maruyama scheme Air passengers - Prophet-like model Analysis of An AR(1) Model in PyMC Variational Inference# Introduction to Variational Inference with PyMC Pathfinder Variational Inference Empirical Approximation overview Variational Inference: Bayesian Neural Networks GLM: Mini-batch ADVI on hierarchical regression model How to# Updating priors Using a custom step method for sampling from locally conjugate posterior distributions Compound Steps in Sampling Sample callback Profiling Lasso regression with block updating How to debug a model Using shared variables (Data container adaptation) Defining a Custom Distribution in PyMC3 General API quickstart
