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icmm  

Empirical Bayes Variable Selection via ICM/M Algorithm
View on CRAN: Click here


Download and install icmm package within the R console
Install from CRAN:
install.packages("icmm")

Install from Github:
library("remotes")
install_github("cran/icmm")

Install by package version:
library("remotes")
install_version("icmm", "1.2")



Attach the package and use:
library("icmm")
Maintained by
Vitara Pungpapong
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-27
Latest Update: 2021-05-26
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.
How to cite:
Vitara Pungpapong (2017). icmm: Empirical Bayes Variable Selection via ICM/M Algorithm. R package version 1.2, https://cran.r-project.org/web/packages/icmm. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:48), 1.0 (2017-07-27 10:42), 1.1 (2017-10-12 05:17)
Other packages that cited icmm R package
View icmm citation profile
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Complete documentation for icmm
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