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
drobust                 pdf of the mixture of the robust emission
                        proposed by Qin et al. (2024)
hhsmmdata               convert to hhsmm data
hhsmmfit                hhsmm model fit
hhsmmspec               hhsmm specification
homogeneity             Computing maximum homogeneity of two state
                        sequences
initial_cluster         initial clustering of the data set
initial_estimate        initial estimation of the model parameters for
                        a specified emission distribution
initialize_model        initialize the hhsmmspec model 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
robust_mstep            the M step function of the EM algorithm
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
