Package: mhsmm 0.4.21

Jared OConnell

mhsmm: Inference for Hidden Markov and Semi-Markov Models

Parameter estimation and prediction for hidden Markov and semi-Markov models for data with multiple observation sequences. Suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.

Authors:Jared O'Connell <[email protected]>, Søren Højsgaard <[email protected]>

mhsmm_0.4.21.tar.gz
mhsmm_0.4.21.tar.gz(r-4.7-arm64)mhsmm_0.4.21.tar.gz(r-4.7-x86_64)mhsmm_0.4.21.tar.gz(r-4.6-arm64)mhsmm_0.4.21.tar.gz(r-4.6-x86_64)
mhsmm_0.4.21.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mhsmm/json (API)

# Install 'mhsmm' in R:
install.packages('mhsmm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • reproai - Artificial insemination times for seven cows
  • reprocows - Reproductive data from seven dairy cows
  • reproppa - Observed lengths of post-partum anoestrus for 73 dairy cows

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.50 score 3 stars 2 packages 87 scripts 547 downloads 1 mentions 34 exports 1 dependencies

Last updated from:6dd5245769. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK118
linux-devel-x86_64OK109
source / vignettesOK182
linux-release-arm64OK136
linux-release-x86_64OK104
wasm-releaseOK102

Exports:addStatescreateTransitiondmvnorm.hsmmdnorm.hsmmdpois.hsmmgammafithmmfithmmspechsmmfithsmmspecmstep.mvnormmstep.normmstep.poisplot.hsmmplot.hsmm.datapredict.hmmpredict.hmmspecpredict.hsmmpredict.hsmmspecpredict.smoothDiscreteprint.hmmprint.hmmspecprint.hsmmspecprint.smoothDiscretermvnorm.hsmmrnorm.hsmmrpois.hsmmsim.mcsimulate.hmmspecsimulate.hsmmspecsmooth.discretesummary.hmmsummary.hsmmsummary.smoothDiscrete

Dependencies:mvtnorm

Smoothing discrete data (I) - smooth.discrete()
Rendered fromDHMM1.Rnwusingutils::Sweave

Last update: 2023-08-23
Started: 2012-09-03

Smoothing discrete data (II)
Rendered fromDHMM2.Rnwusingutils::Sweave

Last update: 2023-08-23
Started: 2012-09-03

Readme and manuals

Help Manual

Help pageTopics
Adds a bar representing state sequence.addStates
Emission ensity function for a multivariate normal emission distributiondmvnorm.hsmm
Emission density function for normal emission distributiondnorm.hsmm
Emission density function for Poisson emission distributiondpois.hsmm
Parameter estimation for the Gamma distributiongammafit
fit a hidden Markov modelhmmfit
Specificatin of HMMshmmspec
fit a hidden semi-Markov modelhsmmfit
Hidden semi-Markov model specificationhsmmspec
Performs re-estimation (the M-step) for a multivariate normal emission distributionmstep.mvnorm
Performs re-estimation (the M-step) for a normal emission distributionmstep.norm
Performs re-estimation (the M-step) for a Poisson emission distributionmstep.pois
Plot function for hsmmsplot.hsmm
Plot function for hsmm dataplot.hsmm.data
Prediction function for hmmpredict.hmm
Prediction function for hmmspecpredict.hmmspec
Prediction for hsmmspredict.hsmm
Prediction for hsmmspecpredict.hsmmspec
Print method for hmm objectsprint.hmm
Print function for hmmspecprint.hmmspec
Print function for hsmmspecprint.hsmmspec
Artificial insemination times for seven cowsreproai
Reproductive data from seven dairy cowsreprocows
Observed lengths of post-partum anoestrus for 73 dairy cowsreproppa
Random number generation from a multivariate normal distributed emission distributionrmvnorm.hsmm
Random number generation from a normally distributed emission distributionrnorm.hsmm
Random number generation from a Poisson distributed emission distributionrpois.hsmm
Markov chain simulationsim.mc
Simulation of hidden Markov modelssimulate.hmmspec
Simulation for HSMMssimulate.hsmmspec
Smoothing a discrete time series.createTransition predict.smoothDiscrete print.smoothDiscrete smooth.discrete summary.smoothDiscrete
Summary method for hmm objectssummary.hmm
Summary function for hsmmsummary.hsmm