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depmixS4 (version 1.0-1)
Dependent Mixture Models - Hidden Markov Models of GLMs and Other Distributions in S4
Description
Fit latent (hidden) Markov models on mixed categorical and continuous (timeseries) data, otherwise known as dependent mixture models
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Install
install.packages('depmixS4')
Monthly Downloads
1,781
Version
1.0-1
License
GPL (>= 2)
Maintainer
Ingmar Visser
Last Published
November 26th, 2010
Functions in depmixS4 (1.0-1)
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GLMresponse
Methods for creating depmix response models
forwardbackward
Forward and backward variables
balance
Balance Scale Data
depmix.sim-class
Class "depmix.sim"
fit
Fit 'depmix' or 'mix' models
depmix-methods
'depmix' and 'mix' methods.
mix
Mixture Model Specifiction
em.control
Control parameters for the EM algorithm
depmix.fitted-class
Class "depmix.fitted"
simulate
Methods to simulate from (dep-)mix models
speed
Speed Accuracy Switching Data
depmix-internal
DepmixS4 internal functions
depmix-class
Class "depmix"
depmixS4-package
depmixS4 provides classes for specifying and fitting hidden Markov models
posterior
Posterior states/classes
mix-class
Class "mix"
llratio
Log likelihood ratio test on two fitted models
makeDepmix
Dependent Mixture Model Specifiction: full control and adding response models
transInit
Methods for creating depmix transition and initial probability models
responses
Response models currently implemented in depmix.
response-classes
Class "GLMresponse" and class "transInit"
mix.fitted-class
Class "mix.fitted"
response-class
Class "response"
mix.sim-class
Class "mix.sim"
depmix
Dependent Mixture Model Specifiction
AIC
Compute AIC and BIC for (dep-)mix objects