summary.plMCMC: Summarizes content of a 'plMCMC' object holding iid copies of...

In EntropyMCMC: MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation

Description

This S3 method for summary summarizes the content of an object of class plMCMC (for parallel MCMC) as returned by, e.g., MCMCcopies, containing the trajectories of iid copies of trajectories from a MCMC algorithm, and its associated kernel, target and proposal densities.

Usage

## S3 method for class 'plMCMC'
summary(object, stats = FALSE, ...)

Arguments

object	An object of class plMCMC as returned by, e.g.,MCMCcopies.
stats	print additional summary statistics for the variables over all chains.
...	additional arguments passed to other methods

Value

Returns the object associated dimensions, the overall rate of acceptation, and descriptive statistics over the variable coordinates if stats = TRUE.

Author(s)

Didier Chauveau.

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.

See Also

MCMCcopies, MCMCcopies.mc

Examples

## See Example for MCMCcopies

EntropyMCMC documentation built on May 2, 2019, 6:43 a.m.