maxLikelihood {BMAmevt}

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