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EntropyMCMC  

MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation
View on CRAN: Click here


Download and install EntropyMCMC package within the R console
Install from CRAN:
install.packages("EntropyMCMC")

Install from Github:
library("remotes")
install_github("cran/EntropyMCMC")

Install by package version:
library("remotes")
install_version("EntropyMCMC", "1.0.4")



Attach the package and use:
library("EntropyMCMC")
Maintained by
Didier Chauveau
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-03-08
Latest Update: 2019-03-08
Description:
Tools for Markov Chain Monte Carlo (MCMC) simulation and performance analysis. Simulate MCMC algorithms including adaptive MCMC, evaluate their convergence rate, and compare candidate MCMC algorithms for a same target density, based on entropy and Kullback-Leibler divergence criteria. MCMC algorithms can be simulated using provided functions, or imported from external codes. This package is based upon work starting with Chauveau, D. and Vandekerkhove, P. (2013) and next articles.
How to cite:
Didier Chauveau (2019). EntropyMCMC: MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation. R package version 1.0.4, https://cran.r-project.org/web/packages/EntropyMCMC. Accessed 09 Oct. 2026.
Previous versions and publish date:
1.0.4 (2019-03-08 18:22), (2026-07-09 08:03)
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Complete documentation for EntropyMCMC
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