Package: icmm
Title: Empirical Bayes Variable Selection via ICM/M Algorithm
Version: 1.2
Authors@R: c(person("Vitara", "Pungpapong", role = c("aut", "cre"),
		     email = "vitara@cbs.chula.ac.th"),
	      person("Min", "Zhang", role = "ctb", email="minzhang@purdue.edu"),
	      person("Dabao", "Zhang", role = "ctb", email = "zhangdb@purdue.edu"))
Author: Vitara Pungpapong [aut, cre],
  Min Zhang [ctb],
  Dabao Zhang [ctb]
Maintainer: Vitara Pungpapong <vitara@cbs.chula.ac.th>
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.
License: GPL (>= 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
Encoding: UTF-8
Imports: EbayesThresh
Suggests: MASS, stats
LazyData: true
RoxygenNote: 7.1.1
Packaged: 2021-05-26 04:52:07 UTC; vpungpap
Repository: CRAN
Date/Publication: 2021-05-26 05:20:02 UTC
NeedsCompilation: no
Built: R 4.6.0; ; 2026-04-27 10:07:04 UTC; unix
