adaptMCMC
Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler
Enables sampling from arbitrary distributions if the log density is known up to a constant; a common situation in the context of Bayesian inference. The implemented sampling algorithm was proposed by Vihola (2012) <DOI:10.1007/s11222-011-9269-5> and achieves often a high efficiency by tuning the proposal distributions to a user defined acceptance rate.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.5 |
rolling linux/jammy R-4.5 | adaptMCMC_1.5.tar.gz |
40.9 KiB |
1.5 |
rolling linux/noble R-4.5 | adaptMCMC_1.5.tar.gz |
40.9 KiB |
1.5 |
rolling source/ R- | adaptMCMC_1.5.tar.gz |
7.1 KiB |
1.5 |
latest linux/jammy R-4.5 | adaptMCMC_1.5.tar.gz |
40.9 KiB |
1.5 |
latest linux/noble R-4.5 | adaptMCMC_1.5.tar.gz |
40.9 KiB |
1.5 |
latest source/ R- | adaptMCMC_1.5.tar.gz |
7.1 KiB |
1.5 |
2026-04-26 source/ R- | adaptMCMC_1.5.tar.gz |
7.1 KiB |
1.5 |
2026-04-23 source/ R- | adaptMCMC_1.5.tar.gz |
7.1 KiB |
1.5 |
2026-04-09 windows/windows R-4.5 | adaptMCMC_1.5.zip |
43.6 KiB |
1.5 |
2025-04-20 source/ R- | adaptMCMC_1.5.tar.gz |
7.1 KiB |