mcmc
Markov Chain Monte Carlo
Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, doi:10.1214/12-AOS1048, function morph.metrop), which achieves geometric ergodicity by change of variable.
- Version0.9-8
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?Yes
- Last release11/16/2023
Documentation
Team
Charles J. Geyer
Leif T. Johnson
Insights
Last 30 days
This package has been downloaded 14,239 times in the last 30 days. That's enough downloads to make it mildly famous in niche technical communities. A badge of honor! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 590 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 167,579 times in the last 365 days. Practically an academic rockstar! That's enough downloads to cause murmurs at international conferences. The day with the most downloads was Jul 12, 2024 with 1,505 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
- Suggests2 packages
- Reverse Imports5 packages
- Reverse Suggests3 packages