Hidden Hybrid Markov/Semi-Markov Model Fitting

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Documentation for package ‘hhsmm’ version 0.3.5

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additive_reg_mstep the M step function of the EM algorithm
addreg_hhsmm_predict predicting the response values for the regime switching model
cov.miss.mix.wt weighted covariance for data with missing values
cov.mix.wt weighted covariance
dmixlm pdf of the mixture of Gaussian linear (Markov-switching) models for hhsmm
dmixmvnorm pdf of the mixture of multivariate normals for hhsmm
dmultinomial.hhsmm pdf of the multinomial emission distribution for hhsmm
dnonpar pdf of the mixture of B-splines for hhsmm
dnorm_additive_reg pdf of the Gaussian additive (Markov-switching) model for hhsmm
hhsmmdata convert to hhsmm data
hhsmmfit hhsmm model fit
hhsmmspec hhsmm specification
homogeneity Computing maximum homogeneity of two state sequences
initialize_model initialize the hhsmmspec model for a specified emission distribution
initial_cluster initial clustering of the data set
initial_estimate initial estimation of the model parameters for a specified emission distribution
lagdata Create hhsmm data of lagged time series
ltr_clus left to right clustering
ltr_reg_clus left to right linear regression clustering
make_model make a hhsmmspec model for a specified emission distribution
miss_mixmvnorm_mstep the M step function of the EM algorithm
mixdiagmvnorm_mstep the M step function of the EM algorithm
mixlm_mstep the M step function of the EM algorithm
mixmvnorm_mstep the M step function of the EM algorithm
mstep.multinomial the M step function of the EM algorithm
nonpar_mstep the M step function of the EM algorithm
predict.hhsmm prediction of state sequence for hhsmm
predict.hhsmmspec prediction of state sequence for hhsmm
raddreg Random data generation from the Gaussian additive (Markov-switching) model for hhsmm model
rmixar Random data generation from the mixture of Gaussian linear (Markov-switching) autoregressive models for hhsmm model
rmixlm Random data generation from the mixture of Gaussian linear (Markov-switching) models for hhsmm model
rmixmvnorm Random data generation from the mixture of multivariate normals for hhsmm model
rmultinomial.hhsmm Random data generation from the multinomial emission distribution for hhsmm model
score the score of new observations
simulate.hhsmmspec Simulation of data from hhsmm model
train_test_split Splitting the data sets to train and test