inmar_hmm_pn2pw: Transform multivariate autoregressive natural parameters to...

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

Transform multivariate autoregressive natural parameters to working parameters

Description

mu and phi do not need to be transformed, as there are no constraints.

Usage

inmar_hmm_pn2pw(m, mu, sigma, gamma, phi, delta = NULL, stationary = TRUE)

Arguments

m	Number of states
mu	List of vectors of length m, means for white noise in each state dependent distribution
sigma	List of vectors of length m, standard deviations for each state dependent multivariate normal distribution
gamma	Transition probabiilty matrix, size m x m
phi	List of k x q matrices, each row contains the autoregressive parameters for a variable.
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.