Package: graper
Type: Package
Title: Adaptive penalization in high-dimensional regression and
        classification with external covariates using variational Bayes
Version: 1.2.0
Authors@R: c(person("Britta", "Velten", email = "britta.velten@embl.de", 
	    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
LazyData: TRUE
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_10
git_last_commit: f14bae8
git_last_commit_date: 2019-10-29
Date/Publication: 2019-10-29
NeedsCompilation: yes
Packaged: 2019-10-30 03:36:10 UTC; biocbuild
Author: Britta Velten [aut, cre],
  Wolfgang Huber [aut]
Maintainer: Britta Velten <britta.velten@embl.de>
Built: R 3.6.1; x86_64-apple-darwin15.6.0; 2019-10-30 12:17:35 UTC; unix
