simulate_initial_probs

simulate_transition_probs

simulate_emission_probs

These are helper functions for quick construction of initial values for various
model building functions.
Mostly useful for global optimization algorithms which do not depend on initial values.

Designed for fitting hidden (latent) Markov models and mixture
hidden Markov models for social sequence data and other categorical time series.
Also some more restricted versions of these type of models are available: Markov
models, 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. The package provides functions for evaluating and comparing
models, as well as functions for visualizing of multichannel sequence data and
hidden Markov models. Models are estimated using maximum likelihood via the EM
algorithm and/or direct numerical maximization with analytical gradients. All
main algorithms are written in C++ with support for parallel computation.
Documentation is available via several vignettes in this page, and the
paper by Helske and Helske (2019, <doi:10.18637/jss.v088.i03>).

Jouni Helske

seqHMM

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

Satu Helske

simulate_initial_probs function

<dl><dt>n_states</dt>
<dd>Number of states in each cluster.</dd>
<dt>n_clusters</dt>
<dd>Number of clusters.</dd>
<dt>left_right</dt>
<dd>Constrain the transition probabilities to upper triangular.
Default is <code>FALSE</code>.</dd>
<dt>diag_c</dt>
<dd>A constant value to be added to diagonal of transition matrices before scaling.</dd>
<dt>n_symbols</dt>
<dd>Number of distinct symbols in each channel.</dd></dl>

Arguments

Simulate Parameters of Hidden Markov Models — simulate_initial_probs

<dl>

<dt>n_states</dt>
<dd>Number of states in each cluster.</dd>


<dt>n_clusters</dt>
<dd>Number of clusters.</dd>


<dt>left_right</dt>
<dd>Constrain the transition probabilities to upper triangular.
Default is <code>FALSE</code>.</dd>


<dt>diag_c</dt>
<dd>A constant value to be added to diagonal of transition matrices before scaling.</dd>


<dt>n_symbols</dt>
<dd>Number of distinct symbols in each channel.</dd>

</dl>

simulate_initial_probs: Simulate Parameters of Hidden Markov Models

Description

Usage

Arguments

See Also