mvnHMM | R Documentation |
Fit multivariate Normal Hidden Markov models by EM.
mvnHMM( y, cl, min.iters = 10, max.iters = 50, tol = 0.001, verbose = interactive() ) gmvnHMM( y, cl, gr, common.transition = FALSE, min.iters = 10, max.iters = 50, tol = 0.001, verbose = interactive() ) grmvnHMM( y, cl, gr, common.transition = FALSE, min.iters = 10, max.iters = 100, tol = 0.001, verbose = interactive() )
y |
the sequence of observations |
cl |
an integer vector allocating observations to classes |
min.iters |
minimum number of EM iterations |
max.iters |
maximum number of EM iterations |
tol |
tolerance for the log likelihood |
verbose |
should the log likelihood be reported. |
gr |
an integer vector allocating observations to groups |
common.transition |
should the transition probabilities be common across groups |
These functions fit K state multivariate Normal hidden Markov
models to sequences of observations. mvnHMM
fits a hidden
Markov model to a single sequence of observations. gmvnHMM
and grmvnHMM
fits separate Markov models to several groups
(sequences) of observations. gmvnHMM
fits a hidden Markov
model to each group so that each state has a different mean across
groups, but a common covariance. grmvnMix
constrains the
means of the states to be Normally distributed across groups.
the fitted model
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