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 |