sqaradap: Illustration of the dangers of doing adaptive MCMC on a noisy...

In mcsm: Functions for Monte Carlo Methods with R

Description

This function constructs a non-parametric proposal after each iteration of the MCMC algorithm, based on the earlier simulations. It shows how poorly this "natural" solution fares.

Usage

sqaradap(T = 10^4, TT = 10^4, scale = 0.5, factor = 1)

Arguments

T	Number of primary MCMC iterations
TT	Number of further adaptive MCMC iterations
scale	Scale of the normal random walk during the first T iterations
factor	Factor of the bw.nrd0(xmc) bandwidth estimation

Value

The function produces two graphs showing the lack of proper fit of the resulting sample.

Author(s)

Christian P. Robert and George Casella

References

Chapter 8 of EnteR Monte Carlo Statistical Methods

See Also

sqar

Examples

sqaradap()

mcsm documentation built on May 2, 2019, 10:16 a.m.