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)... |
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... |
drobust | pdf of the mixture of the robust emission proposed by Qin et... |
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... |
initialize_model | initialize the hhsmmspec model for a specified emission... |
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... |
rmixar | Random data generation from the mixture of Gaussian linear... |
rmixlm | Random data generation from the mixture of Gaussian linear... |
rmixmvnorm | Random data generation from the mixture of multivariate... |
rmultinomial.hhsmm | Random data generation from the multinomial emission... |
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 |
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