mvnorm_hmm_pn2pw: Transform multivariate normal natural parameters to working...

In longjess/hornsharkHMM: Functions For Analysing Horn Shark Data Using Hidden Markov Models

Transform multivariate normal natural parameters to working parameters

Description

mu does not need to be transformed, as there are no constraints. We only need to transform diagonal elements of sigma, since there are no constraints on the covariances. Include only the lower triangular and diagional elements of the sigma matrix, since covariance matrices must be symmetric.

Usage

mvnorm_hmm_pn2pw(m, mu, sigma, gamma, delta = NULL, stationary = TRUE)

Arguments

m	Number of states
mu	List of vectors of length m, means for each state dependent multivariate normal distribution
sigma	List of matrices of size m x m, covariance matrices for each state dependent multivariate normal distribution
gamma	Transition probabiilty matrix, size m x m
delta	Optional, vector of length m containing initial distribution
stationary	Boolean, whether the HMM is stationary or not

Value

Vector of working parameters

longjess/hornsharkHMM documentation built on June 15, 2022, 11:32 p.m.