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Empirical Bayes Variable Selection via ICM/M Algorithm

v1.2 · May 25, 2021 · GPL (>= 2)

Description

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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies EbayesThresh icmm

Version History

new 1.2 Mar 10, 2026