spedygiorgio/markovchain

Python library for analyzing, simulating, and visualizing discrete-time Markov chains and hidden Markov models.

Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences

R package for statistical inference using partially observed Markov processes

Fit hidden Markov models using Template Model Builder (TMB): flexible state-dependent distributions, transition probability structures, random effects, and smoothing splines.

Materials for book: "Markov Chains for programmers"

Probability Distributions as S3 Objects

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

Statistical analysis and visualization of state transition phenomena

A Hidden Markov Model Application and C++ Library for Rapid and Flexible Development of HMMs