Package: HiddenMarkov 1.8-13
David Harte
HiddenMarkov: Hidden Markov Models
Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.
Authors:
HiddenMarkov_1.8-13.tar.gz
HiddenMarkov_1.8-13.tar.gz(r-4.5-noble)HiddenMarkov_1.8-13.tar.gz(r-4.4-noble)
HiddenMarkov_1.8-13.tgz(r-4.4-emscripten)HiddenMarkov_1.8-13.tgz(r-4.3-emscripten)
HiddenMarkov.pdf |HiddenMarkov.html✨
HiddenMarkov/json (API)
NEWS
| # Install 'HiddenMarkov' in R: |
| install.packages('HiddenMarkov', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:661bbcebe1. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 17 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 17 2024 |
Exports:backwardbackward0.mmppBaum.WelchBaum.Welch.mmppBaum.Welch0.mmppBaumWelchbwcontrolcompdeltadmmglmdthmmEstepEstep.mmglm1Estep.mmppEstep0.mmppforwardforward0.mmppforwardbackforwardback.dthmmforwardback.mmpplogLikmmppmchainmmglmmmglm0mmglm1mmglmlong1mmppMstep.betaMstep.binomMstep.expMstep.gammaMstep.glmMstep.lnormMstep.logisMstep.mmglm1Mstep.normMstep.poisneglogLikPi2vectorpmmglmprobhmmQ2vectorresidualshmmsim.hmmsim.hmm1sim.markovsim.mmppvector2Pivector2QViterbiViterbihmm
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Overview of Package HiddenMarkov | HiddenMarkov-package HiddenMarkov |
| Estimation Using Baum-Welch Algorithm | BaumWelch BaumWelch.dthmm BaumWelch.mmglm0 BaumWelch.mmglm1 BaumWelch.mmglmlong1 BaumWelch.mmpp |
| Control Parameters for Baum Welch Algorithm | bwcontrol |
| Changes Made to Package HiddenMarkov | Changes |
| Marginal Distribution of Stationary Markov Chain | compdelta |
| Demonstration Examples | Demonstration |
| Discrete Time HMM Object (DTHMM) | dthmm |
| E-Step of EM Algorithm for DTHMM | Estep |
| Forward and Backward Probabilities of DTHMM | backward forward forwardback forwardback.dthmm |
| Log Likelihood of Hidden Markov Model | logLik logLik.dthmm logLik.mmglm0 logLik.mmglm1 logLik.mmglmlong1 logLik.mmpp |
| Markov Chain Object | mchain |
| Markov Modulated GLM Object | mmglm0 mmglm1 mmglmlong1 |
| Markov Modulated Generalised Linear Model - 2nd Level Functions | Estep.mmglm1 mmglm-2nd-level-functions Mstep.mmglm1 |
| Markov Modulated Poisson Process Object | mmpp |
| Markov Modulated Poisson Process - 2nd Level Functions | Estep.mmpp forwardback.mmpp mmpp-2nd-level-functions |
| M-Step of EM Algorithm for DTHMM | Mstep Mstep.beta Mstep.binom Mstep.exp Mstep.gamma Mstep.glm Mstep.lnorm Mstep.logis Mstep.norm Mstep.pois |
| Negative Log-Likelihood | neglogLik |
| Conditional Distribution Function of DTHMM | probhmm |
| Residuals of Hidden Markov Model | residuals residuals.dthmm residuals.mmglm0 residuals.mmglm1 residuals.mmglmlong1 |
| Simulate Hidden Markov Process | simulate simulate.dthmm simulate.mchain simulate.mmglm0 simulate.mmglm1 simulate.mmglmlong1 simulate.mmpp |
| Summary of Hidden Markov Model | summary summary.dthmm summary.mmglm0 summary.mmglm1 summary.mmglmlong1 summary.mmpp |
| Transform Transition or Rate Matrices to Vector | Pi2vector Q2vector Transform-Parameters vector2Pi vector2Q |
| Viterbi Algorithm for Hidden Markov Model | Viterbi Viterbi.dthmm Viterbi.mmglm0 Viterbi.mmglm1 Viterbi.mmglmlong1 |