luisdamiano/BayesHMM: Full Bayesian Inference for Hidden Markov Models

An R Package to run full Bayesian inference on Hidden Markov Models (HMM) using the probabilistic programming language Stan. The software enables users to fit HMM with time-homogeneous transitions as well as time-varying transition probabilities. Priors can be set for every model parameter. Implemented inference algorithms include forward (filtering), forward-backwards (smoothing), Viterbi (most likely hidden path), prior predictive sampling, and posterior predictive sampling. Graphs, tables and other convenience methods for convergence diagnosis, goodness of fit, and data analysis are provided.

Getting started

Package details

LicenseGPL (>=3)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
luisdamiano/BayesHMM documentation built on May 20, 2019, 2:59 p.m.