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depmixS4 (version 1.0-2)

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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Version

Install

install.packages('depmixS4')

Monthly Downloads

1,630

Version

1.0-2

License

GPL (>= 2)

Maintainer

Ingmar Visser

Last Published

February 18th, 2011

Functions in depmixS4 (1.0-2)

depmix-internal

DepmixS4 internal functions
mix

Mixture Model Specifiction
mix.fitted-class

Class "mix.fitted"
depmix.sim-class

Class "depmix.sim"
responses

Response models currently implemented in depmix.
em.control

Control parameters for the EM algorithm
mix-class

Class "mix"
balance

Balance Scale Data
llratio

Log likelihood ratio test on two fitted models
response-class

Class "response"
mix.sim-class

Class "mix.sim"
depmix

Dependent Mixture Model Specifiction
depmix.fitted-class

Class "depmix.fitted"
AIC

Compute AIC and BIC for (dep-)mix objects
transInit

Methods for creating depmix transition and initial probability models
depmix-methods

'depmix' and 'mix' methods.
depmix-class

Class "depmix"
makeDepmix

Dependent Mixture Model Specifiction: full control and adding response models
speed

Speed Accuracy Switching Data
simulate

Methods to simulate from (dep-)mix models
response-classes

Class "GLMresponse" and class "transInit"
posterior

Posterior states/classes
depmixS4-package

depmixS4 provides classes for specifying and fitting hidden Markov models
fit

Fit 'depmix' or 'mix' models
forwardbackward

Forward and backward variables
GLMresponse

Methods for creating depmix response models