summary.OptimMCL: Summary the output from the iterative procedure of maximising...

In mclcar: Estimating Conditional Auto-Regressive (CAR) Models using Monte Carlo Likelihood Methods

Description

This function summarizes the output of the output from the function OptimMCL.

Usage

## S3 method for class 'OptimMCL'
summary(object, family, trace.all = TRUE, mc.covar =
  TRUE, ...)

Arguments

object	an OptimMCL object returned by OptimMCL.
family	a character takes value in "guass", "binom" and "poisson".
trace.all	an logic value tells whether the input object given by OptimMCL contains results from all iterations of not
mc.covar	if TRUE, the estimated covariance matrix of the MC-MLE is returned
...	arguments passed to or from other methods.

Value

A list containing the following objects:

MC.mle,

the final MC-MLE

N.iter,

the total number of iterations

total.time,

the total time elapsed

convergence,

if TRUE the procedure converges

hessian,

the Hessian at the MC-MLE if given; the default is NULL

mc.covar

the estimated covariance matrix of the MC-MLE if given; the default is NULL

mc.samples

the Monte Carlo samples size used in the initial stage and after the first convergence.

Author(s)

Zhe Sha [e-mail]

See Also

OptimMCL

Examples

## See examples for OptimMCL

Example output

mclcar documentation built on Jan. 8, 2022, 5:07 p.m.