maxLikelihood: Maximum likelihood optimization

In BMAmevt: Multivariate Extremes: Bayesian Estimation of the Spectral Measure

Maximum likelihood optimization

Description

Maximum likelihood optimization

Usage

maxLikelihood(
  data,
  model,
  init = NULL,
  maxit = 500,
  method = "L-BFGS-B",
  hess = T,
  link,
  unlink
)

Arguments

data	The angular data to be used for inference
model	A list made of likelihood The likelihood function, see dpairbeta for a template . npar The length of the parameter vector
init	NULL or a real vector of size model$npar giving the initial values for link{par}.
maxit	maximum number of iterations to be performed by function optim
method	The method to be used by optim
hess	logical: should an approximation of the hessian be performed ?
link	the link function from the natural marginal parameter spaces to the real line.
unlink	the inverse link function. If x is any real number, then unlink(x) should be in the admissible range for the likelihood function and the prior function.

Value

The list returned by optim and the AIC and BIC criteria

BMAmevt documentation built on April 21, 2023, 9:07 a.m.