prob_to_int

<code>prob_to_int</code> transforms a set of state transition or categorical
emission observation probabilities to the corresponding Multinomial logit
regression intercepts. Note that the first category is assumed to be the
reference category, hence no intercept is returned for the first state or
category.

An implementation of the multilevel (also known as mixed or random
effects) hidden Markov model using Bayesian estimation in R. The multilevel
hidden Markov model (HMM) is a generalization of the well-known hidden
Markov model, for the latter see Rabiner (1989) <doi:10.1109/5.18626>. The
multilevel HMM is tailored to accommodate (intense) longitudinal data of
multiple individuals simultaneously, see e.g., de Haan-Rietdijk et al.
<doi:10.1080/00273171.2017.1370364>. Using a multilevel framework, we allow
for heterogeneity in the model parameters (transition probability matrix and
conditional distribution), while estimating one overall HMM. The model can
be fitted on multivariate data with either a categorical, normal, or Poisson
distribution, and include individual level covariates (allowing for e.g.,
group comparisons on model parameters). Parameters are estimated using
Bayesian estimation utilizing the forward-backward recursion within a hybrid
Metropolis within Gibbs sampler. Missing data (NA) in the dependent
variables is accommodated assuming MAR. The package also includes various
visualization options, a function to simulate data, and a function to obtain
the most likely hidden state sequence for each individual using the Viterbi
algorithm.

Emmeke Aarts

mHMMbayes

Multilevel Hidden Markov Models Using Bayesian Estimation

Sebastian Mildiner Moraga

prob_to_int function

<dl><dt>prob_matrix</dt>
<dd>A matrix with number of states OR categories columns and
number of rows to be determined by the user, with rows summing to one. For
obtaining the set of Multinomial logit regression intercepts of the
complete transition probability matrix gamma or categorical emission
distribution matrix, the number of rows equals the number of states
<code>m</code>.</dd></dl>

Arguments

Transforming a set of probabilities to Multinomial logit regression intercepts — prob_to_int

<dl>

<dt>prob_matrix</dt>
<dd>A matrix with number of states OR categories columns and
number of rows to be determined by the user, with rows summing to one. For
obtaining the set of Multinomial logit regression intercepts of the
complete transition probability matrix gamma or categorical emission
distribution matrix, the number of rows equals the number of states
<code>m</code>.</dd>

</dl>

prob_to_int: Transforming a set of probabilities to Multinomial logit regression intercepts

Description

Usage

Value

Arguments

Details

See Also

Examples