pypomp documentation

Version: 0.4.8 Date: July 20, 2026

Pypomp is a Python package for modeling and inference using partially observed Markov process (POMP) models, also called state-space models (SSM) or hidden Markov models (HMM). Key features include:

  • Estimation, filtering, and inference for nonlinear, non-Gaussian POMP models via the particle filter

  • GPU support and just-in-time compilation via JAX, enabling significant speedups

  • New algorithms for model-fitting with gradient descent using improved gradient estimates

  • Support for both standard POMP models and panel POMP models

Installation

You can install Pypomp from PyPI:

pip install pypomp              # install with core dependencies
pip install pypomp[benchmarks]  # install with packages for log-likelihood benchmarking
pip install pypomp[viz]         # install with plot dependencies

To install the latest development branch:

pip install git+https://github.com/pypomp/pypomp.git

Pypomp depends on JAX. To take full advantage of GPU acceleration, we highly recommend installing the GPU-enabled version of JAX. Please refer to the JAX installation guide for detailed instructions specific to your system.

Contents

Getting Started

Reference

Resources

Indices