gam_viterbi: Global decoding by the Viterbi algorithm

In simonecollier/lizardHMM: Fitting Lizard Movement Data with HMMs

Description

This function takes in data x assumed to be generated by the HMM hmm and outputs the most likely sequence of states that could have generated the data using global decoding by the Viterbi algorithm.

Usage

gam_viterbi(x, hmm, state_dep_dist_pooled = FALSE)

Arguments

x	The data to be fit with an HMM in the form of a 3D array. The first index (row) corresponds to time, the second (column) to the variable number, and the third (matrix number) to the subject number.
hmm	A list of parameters that specify the gamma HMM, including num_states, num_variables, num_subjects, num_covariates, alpha, theta, gamma, delta.
state_dep_dist_pooled	A logical variable indiacting whether the state dependent distribution parameters alpha and theta should be treated as equal for all subjects.

Value

A matrix with each column containing the sequence of states for the given subject.

simonecollier/lizardHMM documentation built on Dec. 23, 2021, 2:24 a.m.