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rarhsmm (version 1.0.7)

Regularized Autoregressive Hidden Semi Markov Model

Description

Fit Gaussian hidden Markov (or semi-Markov) models with / without autoregressive coefficients and with / without regularization. The fitting algorithm for the hidden Markov model is illustrated by Rabiner (1989) . The shrinkage estimation on the covariance matrices is based on the method by Ledoit et al. (2004) . The shrinkage estimation on the autoregressive coefficients uses the elastic net shrinkage detailed in Zou et al. (2005) .

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Version

Install

install.packages('rarhsmm')

Monthly Downloads

27

Version

1.0.7

License

GPL

Maintainer

Zekun Xu

Last Published

March 20th, 2018

Functions in rarhsmm (1.0.7)

mvdnorm

multivariate normal density
package-rarhsmm

Regularized Autoregressive Hidden Semi Markov Models
em.hmm

EM algorithm to compute maximum likelihood estimate of Gaussian hidden Markov models with / without autoregressive structures and with / without regularization on the covariance matrices and/or autoregressive structures.
hmm.predict

1-step forward prediction for (autoregressive) Gaussian hidden Markov model
em.semi

EM algorithm to compute maximum likelihood estimate of Gaussian hidden semi-Markov models with / without autoregressive structures and with / without regularization on the covariance matrices and/or autoregressive structures.
hsmm.predict

1-step forward prediction for (autoregressive) Gaussian hidden semi-Markov model
rmultinomial

multinomial random variable generator
hmm.sim

Simulate a Gaussian hidden Markov series with / without autoregressive structures
hsmm.sim

Simulate a Gaussian hidden semi-Markov series with / without autoregressive structures
finance

NYSE stock closing price data
mvrnorm

multivariate normal random number generator
smooth.hmm

Calculate the probability of being in a particular state for each observation.
smooth.semi

Calculate the probability of being in a particular state for each observation.
viterbi.semi

Viterbi algorithm to decode the latent states for Gaussian hidden semi-Markov model with / without autoregressive structures
viterbi.hmm

Viterbi algorithm to decode the latent states for Gaussian hidden Markov model with / without autoregressive structures