mcsm (version 1.0)

sqaradap: Illustration of the dangers of doing adaptive MCMC on a noisy squared AR model

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.

References

Chapter 8 of EnteR Monte Carlo Statistical Methods

See Also

sqar

Examples

sqaradap()