tmcmc_metrop: Simulate a Transformation based Markov Chain Monte Carlo...

Description Usage Arguments Value

Description

The function simulates a TMCMC chain of length nsamples using the scale, base and burn in taken optimally as default or specified by user. The function outputs the full chain as well as the estimated posterior mean estimated from the samples drawn post burn-in.

Usage

1
tmcmc_metrop(target_pdf, scale, base, nsamples, burn_in = NULL, verb = TRUE)

Arguments

target_pdf

The log target density function from which the user wants to generate samples.

scale

The proposal density scaling parameter. An approximation of the optimal scaling given the target_pdf is performed by OptimalScaling(). The default scale is this estimated optimal scaling

base

The starting value of the chain

nsamples

The number of samples to be drawn using the TMCMC algorithm.

burn_in

The number of samples assigned as burn-in period. The default burn-in is taken to be one-third of nsamples.

verb

logical parameter, if TRUE the function prints the progress of simulation.

Value

Returns a list containing the following items

chain

The full chain produced by the TMCMC method.

post.mean

The estimated posterior mean of the TMCMC chain adjusting for burn-in.

@author Kushal K Dey

@useDynLib tmcmcR2 @import tmcmcR2 @export


kkdey/tmcmcR2 documentation built on May 20, 2019, 10:40 a.m.