{"id":16499448,"url":"https://github.com/tpapp/hiddenmarkovchains.jl","last_synced_at":"2025-03-01T18:21:05.350Z","repository":{"id":55588555,"uuid":"68203650","full_name":"tpapp/HiddenMarkovChains.jl","owner":"tpapp","description":"Hidden Markov Chain calculations in Julia","archived":false,"fork":false,"pushed_at":"2020-12-20T09:15:19.000Z","size":27,"stargazers_count":4,"open_issues_count":3,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-28T16:20:11.246Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Julia","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tpapp.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-09-14T12:18:22.000Z","updated_at":"2019-07-05T01:44:40.000Z","dependencies_parsed_at":"2022-08-15T03:50:21.985Z","dependency_job_id":null,"html_url":"https://github.com/tpapp/HiddenMarkovChains.jl","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpapp%2FHiddenMarkovChains.jl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpapp%2FHiddenMarkovChains.jl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpapp%2FHiddenMarkovChains.jl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpapp%2FHiddenMarkovChains.jl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tpapp","download_url":"https://codeload.github.com/tpapp/HiddenMarkovChains.jl/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241405079,"owners_count":19957764,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T14:52:56.147Z","updated_at":"2025-03-01T18:21:05.326Z","avatar_url":"https://github.com/tpapp.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# HiddenMarkovChains — a Julia library\n\n[![Project Status: WIP - Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](http://www.repostatus.org/badges/latest/wip.svg)](http://www.repostatus.org/#wip)\n[![Build Status](https://travis-ci.org/tpapp/HiddenMarkovChains.jl.svg?branch=master)](https://travis-ci.org/tpapp/HiddenMarkovChains.jl)\n[![Coverage Status](https://coveralls.io/repos/tpapp/HiddenMarkovChains.jl/badge.svg?branch=master\u0026service=github)](https://coveralls.io/github/tpapp/HiddenMarkovChains.jl?branch=master)\n[![codecov.io](http://codecov.io/github/tpapp/HiddenMarkovChains.jl/coverage.svg?branch=master)](http://codecov.io/github/tpapp/HiddenMarkovChains.jl?branch=master)\n\nThis is a preliminary collection of functions I use for calculations that involve Hidden Markov Chains (HMC). It is mainly used for\n\n1. [indirect inference](http://www.econ.yale.edu/smith/palgrave7.pdf) for macroeconomic models, in which the state space is discretized. Exact calculation of path probabilities allows smooth functions of model parameters, obviating the need for [explicit smoothing](http://arxiv.org/abs/1507.06115) (of course discretization brings in another set of problems), and\n\n2. likelihood-based methods, such as Bayesian MCMC, with HMCs. The library implements numerically stable calculation of log likelihoods for observed sequences.\n\n*Tamas K. Papp acknowledges support from the Jubiläumsfonds grant (16256) of the Austrian National Bank.*\n\n## Bibliography\n\n*Golub, Gene H., and Carl D. Meyer, Jr.* \"Using the QR factorization and group inversion to compute, differentiate, and estimate the sensitivity of stationary probabilities for Markov chains.\" SIAM Journal on Algebraic Discrete Methods 7.2 (1986): 273-281.\n\n*Rabiner, Lawrence R.* \"A tutorial on hidden Markov models and selected applications in speech recognition.\" Proceedings of the IEEE 77.2 (1989): 257-286.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftpapp%2Fhiddenmarkovchains.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftpapp%2Fhiddenmarkovchains.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftpapp%2Fhiddenmarkovchains.jl/lists"}