metropolis
The Metropolis Algorithm
Learning and using the Metropolis algorithm for Bayesian fitting of a generalized linear model. The package vignette includes examples of hand-coding a logistic model using several variants of the Metropolis algorithm. The package also contains R functions for simulating posterior distributions of Bayesian generalized linear model parameters using guided, adaptive, guided-adaptive and random walk Metropolis algorithms. The random walk Metropolis algorithm was originally described in Metropolis et al (1953); <doi:10.1063/1.1699114>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.8 |
rolling linux/jammy R-4.5 | metropolis_0.1.8.tar.gz |
649.5 KiB |
0.1.8 |
rolling linux/noble R-4.5 | metropolis_0.1.8.tar.gz |
649.5 KiB |
0.1.8 |
rolling source/ R- | metropolis_0.1.8.tar.gz |
618.2 KiB |
0.1.8 |
latest linux/jammy R-4.5 | metropolis_0.1.8.tar.gz |
649.5 KiB |
0.1.8 |
latest linux/noble R-4.5 | metropolis_0.1.8.tar.gz |
649.5 KiB |
0.1.8 |
latest source/ R- | metropolis_0.1.8.tar.gz |
618.2 KiB |
0.1.8 |
2026-04-26 source/ R- | metropolis_0.1.8.tar.gz |
618.2 KiB |
0.1.8 |
2026-04-23 source/ R- | metropolis_0.1.8.tar.gz |
618.2 KiB |
0.1.8 |
2026-04-09 windows/windows R-4.5 | metropolis_0.1.8.zip |
654.7 KiB |
0.1.8 |
2025-04-20 source/ R- | metropolis_0.1.8.tar.gz |
618.2 KiB |