fit_tpm: Compute transition probability matrices

In simonecollier/lizardHMM: Fitting Lizard Movement Data with HMMs

Description

This function computes the time dependent transition probability matrix from the corresponding vector design and the matrix of regression coefficients beta.

Usage

fit_tpm(num_states, num_subjects, num_covariates, num_time, beta, design)

Arguments

num_states	The number of states in the desired HMM.
num_subjects	The number of subjects/trials that generated the data.
num_covariates	The number of covariates in the data that the transition probability matrix depends on.
num_time	A value indicating the length of the data.
beta	A matrix of regression coefficients for the effect of the covariates on the transition probability matrices gamma.
design	A list of design matrices, one for each subject which indicate the values of the each of the covariates (column) at each point in time (row).

Value

A list containing a list for each subject/trial of the transition probability matrices at each time step.

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