PrevMap (version 1.5.4)

control.mcmc.MCML: Control settings for the MCMC algorithm used for classical inference on a binomial logistic model

Description

This function defines the options for the MCMC algorithm used in the Monte Carlo maximum likelihood method.

Usage

control.mcmc.MCML(n.sim, burnin, thin = 1, h = NULL, c1.h = 0.01, c2.h = 1e-04)

Arguments

n.sim

number of simulations.

burnin

length of the burn-in period.

thin

only every thin iterations, a sample is stored; default is thin=1.

h

tuning parameter of the proposal distribution used in the Langevin-Hastings MCMC algorithm (see Laplace.sampling and Laplace.sampling.lr); default is h=NULL and then set internally as \(1.65/n^(1/6)\), where \(n\) is the dimension of the random effect.

c1.h

value of \(c_{1}\) used in the adaptive scheme for h; default is c1.h=0.01. See also 'Details' in binomial.logistic.MCML

c2.h

value of \(c_{2}\) used in the adaptive scheme for h; default is c1.h=0.01. See also 'Details' in binomial.logistic.MCML

Value

A list with processed arguments to be passed to the main function.

Examples

# NOT RUN {
control.mcmc <- control.mcmc.MCML(n.sim=1000,burnin=100,thin=1,h=0.05)
str(control.mcmc)
# }