trMatrix_rcpp

Computation of the transition probability matrix, as a function of the covariates and the regression
parameters. Written in C++. Used in <code>viterbi</code>.

Extended tools for analyzing telemetry data using generalized hidden Markov models. Features of momentuHMM (pronounced ``momentum'') include data pre-processing and visualization, fitting HMMs to location and auxiliary biotelemetry or environmental data, biased and correlated random walk movement models, hierarchical HMMs, multiple imputation for incorporating location measurement error and missing data, user-specified design matrices and constraints for covariate modelling of parameters, random effects, decoding of the state process, visualization of fitted models, model checking and selection, and simulation. See McClintock and Michelot (2018) <doi:10.1111/2041-210X.12995>.

Brett T McClintock

momentuHMM

Maximum Likelihood Analysis of Animal Movement Behavior Using
Multivariate Hidden Markov Models

trMatrix_rcpp function

<dl><dt>nbStates</dt>
<dd>Number of states</dd>
<dt>beta</dt>
<dd>Matrix of regression parameters</dd>
<dt>covs</dt>
<dd>Matrix of covariate values</dd>
<dt>betaRef</dt>
<dd>Indices of reference elements for t.p.m. multinomial logit link.</dd></dl>

Arguments

Transition probability matrix — trMatrix_rcpp

<dl>

<dt>nbStates</dt>
<dd>Number of states</dd>


<dt>beta</dt>
<dd>Matrix of regression parameters</dd>


<dt>covs</dt>
<dd>Matrix of covariate values</dd>


<dt>betaRef</dt>
<dd>Indices of reference elements for t.p.m. multinomial logit link.</dd>

</dl>

trMatrix_rcpp: Transition probability matrix

Description

Usage

Value

Arguments