logLik.hmm

logLik.mhmm

Log-likelihood of a Hidden Markov Model

Designed for estimating variants of hidden (latent) Markov models
(HMMs), mixture HMMs, and non-homogeneous HMMs (NHMMs) for social sequence
data and other categorical time series. Special cases include
feedback-augmented NHMMs, Markov models without latent layer, mixture
Markov models, and latent class models. The package supports models for one
or multiple subjects with one or multiple parallel sequences (channels).
External covariates can be added to explain cluster membership in mixture
models as well as initial, transition and emission probabilities in NHMMs.
The package provides functions for evaluating and comparing models, as well
as functions for visualizing of multichannel sequence data and HMMs. For
NHMMs, methods for computing average causal effects and marginal state and
emission probabilities are available. Models are estimated using maximum
likelihood via the EM algorithm or direct numerical maximization with
analytical gradients. Documentation is available via several vignettes,
and Helske and Helske (2019, <doi:10.18637/jss.v088.i03>). For methodology
behind the NHMMs, see Helske (2025, <doi:10.48550/arXiv.2503.16014>).

Jouni Helske

seqHMM

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

Satu Helske

logLik.hmm function

<dl><dt>object</dt>
<dd>A hidden Markov model.</dd>
<dt>partials</dt>
<dd>Return a vector containing the individual contributions of
each sequence to the total log-likelihood. The default is <code>FALSE</code>, which
returns the sum of all log-likelihood components.</dd>
<dt>threads</dt>
<dd>Number of threads to use in parallel computing. The default
is 1.</dd>
<dt>log_space</dt>
<dd>Make computations using log-space instead of scaling for
greater numerical stability at the cost of decreased computational
performance. The default is <code>FALSE</code>.</dd>
<dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Log-likelihood of a Hidden Markov Model — logLik.hmm

<dl>

<dt>object</dt>
<dd>A hidden Markov model.</dd>


<dt>partials</dt>
<dd>Return a vector containing the individual contributions of
each sequence to the total log-likelihood. The default is <code>FALSE</code>, which
returns the sum of all log-likelihood components.</dd>


<dt>threads</dt>
<dd>Number of threads to use in parallel computing. The default
is 1.</dd>


<dt>log_space</dt>
<dd>Make computations using log-space instead of scaling for
greater numerical stability at the cost of decreased computational
performance. The default is <code>FALSE</code>.</dd>


<dt>...</dt>
<dd>Ignored.</dd>

</dl>

logLik.hmm: Log-likelihood of a Hidden Markov Model

Description

Usage

Value

Arguments