mar_hmm_mle: Maximum likelihood estimation of multivariate normal...

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

Maximum likelihood estimation of multivariate normal parameters

Description

Maximum likelihood estimation of multivariate normal parameters

Usage

mar_hmm_mle(
  x,
  m,
  q,
  k,
  mu0,
  sigma0,
  gamma0,
  phi0,
  delta0 = NULL,
  stationary = TRUE,
  hessian = FALSE
)

Arguments

x	Matrix of observations, rows represent each variable
m	Number of states
mu0	List of vectors of length m, initial values for means for white noise
sigma0	List of matrices of size m x m, initial values for covariance matrices
gamma0	Initial values for ransition probabiilty matrix, size m x m
phi0	List of matrices of size k x (k x q), initial values for autoregressive parameters
delta0	Optional, vector of length m containing initial values initial distribution
stationary	Boolean, whether the HMM is stationary or not
hessian	Boolean, whether to return the inverse hessian

Value

List of results

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