Package: graper
Type: Package
Title: Adaptive penalization in high-dimensional regression and
        classification with external covariates using variational Bayes
Version: 1.12.0
Authors@R: c(person("Britta", "Velten", email = "britta.velten@gmail.com", 
	    role = c("aut", "cre")),
	person("Wolfgang", "Huber", role=c("aut"), email="wolfgang.huber@embl.de"))
Date: 2018-10-26
License: GPL (>= 2)
Description: This package enables regression and classification on high-dimensional data with different relative strengths of penalization for different feature groups, such as different assays or omic types. The optimal relative strengths are chosen adaptively. Optimisation is performed using a variational Bayes approach. 
Depends: R (>= 3.6)
Encoding: UTF-8
Imports: Matrix, Rcpp, stats, ggplot2, methods, cowplot, matrixStats
LinkingTo: Rcpp, RcppArmadillo, BH
biocViews: Regression, Bayesian, Classification
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, BiocStyle, testthat
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/graper
git_branch: RELEASE_3_15
git_last_commit: d7ee5fa
git_last_commit_date: 2022-04-26
Date/Publication: 2022-04-26
NeedsCompilation: yes
Packaged: 2022-04-26 23:08:16 UTC; biocbuild
Author: Britta Velten [aut, cre],
  Wolfgang Huber [aut]
Maintainer: Britta Velten <britta.velten@gmail.com>
Built: R 4.2.0; x86_64-w64-mingw32; 2022-04-27 09:34:44 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
