Hierarchical Dirichlet Process Hidden Markov Models in Julia.
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
docs
src
test Use HMMBase Jan 7, 2019
.gitignore
.travis.yml Enable doc. deployment Feb 1, 2019
LICENSE
Project.toml
README.md Update README.md Feb 15, 2019

README.md

HDPHMM.jl

Hierarchical Dirichlet Process Hidden Markov Models in Julia.

Documentation Build Status

Introduction

This is a Julia 1.0+ implementation of the blocked Gibbs sampler [1] for the sticky HDP-HMM with parametric and nonparametric (DPMM) emission models. This is a work in progress, in the meantime you may want to check a more complete and stable implementation such as pyhsmm.

[1] Fox, E. B., Sudderth, E. B., Jordan, M. I., & Willsky, A. S. (2007). The sticky HDP-HMM: Bayesian nonparametric hidden Markov models with persistent states. (PDF)

Installation

The package can be installed with the Julia package manager. From the Julia REPL, type ] to enter the Pkg REPL mode and run:

pkg> registry add https://github.com/maxmouchet/JuliaRegistry.git
pkg> add HDPHMM

Documentation

  • STABLEdocumentation of the most recently tagged version.
  • DEVELdocumentation of the in-development version.

Project Status

The package is tested against Julia 1.0 and the nightly builds of the Julia master branch on Linux.

Questions and Contributions

Contributions are very welcome, as are feature requests and suggestions. Please open an issue if you encounter any problems.