reglogit
Simulation-Based Regularized Logistic Regression
Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface. For details, see Gramacy & Polson (2012 <doi:10.1214/12-BA719>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2-8 |
rolling linux/jammy R-4.5 | reglogit_1.2-8.tar.gz |
96.1 KiB |
1.2-8 |
rolling linux/noble R-4.5 | reglogit_1.2-8.tar.gz |
96.1 KiB |
1.2-8 |
rolling source/ R- | reglogit_1.2-8.tar.gz |
34.6 KiB |
1.2-8 |
latest linux/jammy R-4.5 | reglogit_1.2-8.tar.gz |
96.1 KiB |
1.2-8 |
latest linux/noble R-4.5 | reglogit_1.2-8.tar.gz |
96.1 KiB |
1.2-8 |
latest source/ R- | reglogit_1.2-8.tar.gz |
34.6 KiB |
1.2-8 |
2026-04-26 source/ R- | reglogit_1.2-8.tar.gz |
34.6 KiB |
1.2-8 |
2026-04-23 source/ R- | reglogit_1.2-8.tar.gz |
34.6 KiB |
1.2-8 |
2026-04-09 windows/windows R-4.5 | reglogit_1.2-8.zip |
218.4 KiB |
1.2-7 |
2025-04-20 source/ R- | reglogit_1.2-7.tar.gz |
34.4 KiB |