seqHMM: mc_to_sc – R documentation

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mc_to_sc

Transform a Multichannel Hidden Markov Model into a Single Channel Representation

Description

Transforms data and parameters of a multichannel model into a single channel model. Observed states (symbols) are combined and parameters multiplied across channels.

Usage

mc_to_sc(model, combine_missing = TRUE, all_combinations = FALSE)

Arguments

`model`	An object of class `hmm` or `mhmm`.
`combine_missing`	Controls whether combined states of observations at time t are coded missing (coded with * in `stslist`s) if one or more of the channels include missing information at time t. Defaults to `TRUE`. `FALSE` keeps missing states as they are, producing more states in data; e.g. single/childless/* where the observation in channel 3 is missing.
`all_combinations`	Controls whether all possible combinations of observed states are included in the single channel representation or only combinations that are found in the data. Defaults to `FALSE`, i.e. only actual observations are included.

Details

Note that in case of no missing observations, the log-likelihood of the original and transformed models are identical but the AIC and BIC can be different as the model attribute df is recomputed based on the single channel representation.

Examples

# Loading a hidden Markov model of the biofam data (hmm object)
data("hmm_biofam")

# Convert the multichannel model to a single-channel model
sc <- mc_to_sc(hmm_biofam)

# Likelihoods of the single-channel and the multichannel model are the same
# (Might not be true if there are missing observations)
logLik(sc)
logLik(hmm_biofam)

seqHMM

Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

v1.0.14

GPL (>= 2)

Authors

Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Satu Helske [aut] (<https://orcid.org/0000-0003-0532-0153>)

Initial release

2019-10-21