R: Hidden Hybrid Markov/Semi-Markov Model Fitting

# Hidden Hybrid Markov/Semi-Markov Model Fitting

## Documentation for package ‘hhsmm’ version 0.4.2

- DESCRIPTION file

## Help Pages

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
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
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