ar_hmm_mle: Maximum likelihood estimation of univariate autoregresive...

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

Maximum likelihood estimation of univariate autoregresive parameters

Description

Maximum likelihood estimation of univariate autoregresive parameters

Usage

ar_hmm_mle(
  x,
  m,
  q,
  mu0,
  sigma0,
  gamma0,
  phi0,
  delta0 = NULL,
  stationary = TRUE,
  hessian = FALSE,
  steptol = 1e-06,
  iterlim = 100,
  stepmax = 100,
  state = NULL
)

Arguments

x	Vector of observations
m	Number of states
mu0	Vector of length m, initial values for means the white noise
sigma0	Vector of length m, initial values for standard deviations
gamma0	Matrix of size m x m, initial values for transition probability matrix
phi0	Matrix of size m x q, initial values for autoregressive parameters
delta0	Optional, vector of length m, initial values for initial distribution
stationary	Boolean, whether the HMM is stationary or not
hessian	Boolean, whether to return the inverse hessian
state	List of state values, if provided. 0 represents an unknown state value.

Value

List of results

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