Title: Feature Selection for High Dimensional Survival Data
Package: highMLR
Version: 0.1.1
Date: 2022-07-17
Depends: R (>= 3.5.0)
Imports: mlr3, mlr3learners, survival, gtools, tibble, dplyr, utils,
        coxme, missForest, R6
LazyData: Yes
LazyDataCompression: xz
ByteCompile: Yes
Authors@R: c(person(("Atanu"), "Bhattacharjee",
                    email="atanustat@gmail.com",
	            role=c("aut", "cre","ctb")),
	            person(("Gajendra"), "K. Vishwakarma", role=c("aut","ctb")),
	            person(("Souvik"),"Banerjee", role=c("aut","ctb")))
Description: Perform high dimensional Feature Selection in the presence of survival outcome.
            Based on Feature Selection method and different survival analysis, it will obtain the best 
            markers with optimal threshold levels according to their effect on disease progression
            and produce the most consistent level according to those threshold values. 
            The functions' methodology is based on by Sonabend et al (2021) <doi:10.1093/bioinformatics/btab039>  and Bhattacharjee  et al (2021) <arXiv:2012.02102>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Maintainer: Atanu Bhattacharjee <atanustat@gmail.com>
RoxygenNote: 7.2.0
Packaged: 2022-07-16 22:31:58 UTC; atanu
Author: Atanu Bhattacharjee [aut, cre, ctb],
  Gajendra K. Vishwakarma [aut, ctb],
  Souvik Banerjee [aut, ctb]
Repository: CRAN
Date/Publication: 2022-07-18 08:10:08 UTC
Built: R 4.6.0; ; 2026-04-26 13:26:40 UTC; unix
