EntropyMCMC
MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation
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) doi:10.1051/ps/2012004 and next articles.
- Version1.0.4
- R version≥ 3.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release03/08/2019
Documentation
Team
Didier Chauveau
Houssam Alrachid
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 148 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,222 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 22, 2024 with 33 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Suggests2 packages