mcl.HCAR

parameter values at which the Monte Carlo likelihood function to be evaluated

pars

The Monte Carlo sample object returned by the function <code><a rd-options="" href="/link/sim.HCAR?package=mclcar&version=0.2-0" data-mini-rdoc="mclcar::sim.HCAR">sim.HCAR</a></code>

mcdata

A list or an environment containing the same variables same as the input for <code><a rd-options="" href="/link/sim.HCAR?package=mclcar&version=0.2-0" data-mini-rdoc="mclcar::sim.HCAR">sim.HCAR</a>,</code>

data

If true, the Monte Carlo variance is evaluated.

Evar

Evaluate the Monte Carlo likelihood of a hierarchical conditional-autoregressive model at a given parameter value and importance sampler value.

The likelihood of direct CAR models and Binomial and Poisson GLM with latent CAR variables are approximated by the Monte Carlo likelihood. The Maximum Monte Carlo likelihood estimator is found either by an iterative procedure of directly maximising the Monte Carlo approximation or by a response surface design method.Reference for the method can be found in the DPhil thesis in Z. Sha (2016). For application a good reference is R.Bivand et.al (2017) <doi:10.1016/j.spasta.2017.01.002>.

Zhe Sha

mclcar

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

mcl.HCAR function

The Monte Carlo sample object returned by the function <code><a rd-options='' href='sim.HCAR'>sim.HCAR</a></code>

A list or an environment containing the same variables same as the input for <code><a rd-options='' href='sim.HCAR'>sim.HCAR</a>,</code>

mcl.HCAR: The Monte Carlo likelihood function of the HCAR model.

Description

Usage

Arguments

Value

See Also