icmm
Empirical Bayes Variable Selection via ICM/M Algorithm
Empirical Bayes variable selection via ICM/M algorithm for normal, binary logistic, and Cox's regression. The basic problem is to fit high-dimensional regression which sparse coefficients. This package allows incorporating the Ising prior to capture structure of predictors in the modeling process. More information can be found in the papers listed in the URL below.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2 |
rolling linux/jammy R-4.5 | icmm_1.2.tar.gz |
986.2 KiB |
1.2 |
rolling linux/noble R-4.5 | icmm_1.2.tar.gz |
986.2 KiB |
1.2 |
rolling source/ R- | icmm_1.2.tar.gz |
923.1 KiB |
1.2 |
latest linux/jammy R-4.5 | icmm_1.2.tar.gz |
986.2 KiB |
1.2 |
latest linux/noble R-4.5 | icmm_1.2.tar.gz |
986.2 KiB |
1.2 |
latest source/ R- | icmm_1.2.tar.gz |
923.1 KiB |
1.2 |
2026-04-26 source/ R- | icmm_1.2.tar.gz |
923.1 KiB |
1.2 |
2026-04-23 source/ R- | icmm_1.2.tar.gz |
923.1 KiB |
1.2 |
2026-04-09 windows/windows R-4.5 | icmm_1.2.zip |
989.6 KiB |
1.2 |
2025-04-20 source/ R- | icmm_1.2.tar.gz |
923.1 KiB |