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.

Package details

AuthorVitara Pungpapong [aut, cre], Min Zhang [ctb], Dabao Zhang [ctb]
MaintainerVitara Pungpapong <vitara@cbs.chula.ac.th>
LicenseGPL (>= 2)
URL https://www.researchgate.net/publication/279279744_Selecting_massive_variables_using_an_iterated_conditional_modesmedians_algorithm https://doi.org/10.1089/cmb.2019.0319
Package repositoryView on CRAN
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icmm documentation built on May 26, 2021, 9:06 a.m.