plot.KbMCMC: Plot sequences of estimates of Kullback distance or Entropy against iterations

Description

This S3 method for plot plots by default sequences of estimates of the Kullback distance \(K(p^t,f)\) between the (estimated) pdf of the MCMC algorithm at time \(t\), \(p^t\), and the target density \(f\), for \(t=1\) up to the number of iterations that have been provided/computed. It can also plot the first term in the Kullback distance, i.e. the Entropy \(E_{p^t}[\log(p^t)]\). Its argument is an object of class KbMCMC such as the one returned by, e.g., EntropyMCMC.

Usage

# S3 method for KbMCMC
plot(x, Kullback = TRUE, lim = NULL, ylim = NULL, 
            new.plot = TRUE, title = NULL, ...)

Arguments

An object of class KbMCMC, such as the one returned by EntropyMCMC.

Kullback

TRUE to plot the Kullback distance, FALSE to plot the Entropy.

lim

for zooming over 1:lim iterations only.

ylim

y limits, passed to plot.

new.plot

set to FALSE to add the plot to an existing plot.

title

The title; if NULL, then a default title is displayed.

…

Further parameters passed to plot or lines.

Value

The graphic to plot.

References

Chauveau, D. and Vandekerkhove, P. (2012), Smoothness of Metropolis-Hastings algorithm and application to entropy estimation. ESAIM: Probability and Statistics, 17, (2013) 419--431. DOI: http://dx.doi.org/10.1051/ps/2012004
Chauveau D. and Vandekerkhove, P. (2014), Simulation Based Nearest Neighbor Entropy Estimation for (Adaptive) MCMC Evaluation, In JSM Proceedings, Statistical Computing Section. Alexandria, VA: American Statistical Association. 2816--2827.
Chauveau D. and Vandekerkhove, P. (2014), The Nearest Neighbor entropy estimate: an adequate tool for adaptive MCMC evaluation. Preprint HAL http://hal.archives-ouvertes.fr/hal-01068081.

Examples

Run this code

# NOT RUN {
## See the EntropyMCMC Examples.
# }