Hidden Markov Models Python Packages

h2mm-c

Photon By Photon Hidden Markov Modeling scripts based on Pirchi et. al. JPC 2016, 120, 13065, extended in Multi-parameter photon-by-photon hidden Markov modeling, Harris, P.D., Narducci, A., Gebhardt, C. et al. Multi-parameter photon-by-photon Hidden Markov Modeling. Nat Commun 13, 1000 (2022).

dynamax

A Python package for probabilistic state space modeling with JAX

smcx

Sequential inference for state-space models in JAX: Kalman-family filters and smoothers, and SMC methods including particle filters, tempered SMC, and SMC².

regimelab

Institutional-grade market regime detection, systemic risk telemetry, and walk-forward backtesting engine in Python.

sequentia

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

numpy-ml

Machine learning, in numpy

bhmm

Bayesian hidden Markov models toolkit

smcjax

Sequential inference for state-space models in JAX: Kalman-family filters and smoothers, and SMC methods including particle filters, tempered SMC, and SMC².

latentflow

A Python package for estimating and simulating latent variable models