DOI: 10.18129/B9.bioc.graper  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see graper.

Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes

Bioconductor version: 3.16

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.

Author: Britta Velten [aut, cre], Wolfgang Huber [aut]

Maintainer: Britta Velten <britta.velten at>

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biocViews Bayesian, Classification, Regression, Software
Version 1.14.2
In Bioconductor since BioC 3.9 (R-3.6) (4 years)
License GPL (>= 2)
Depends R (>= 3.6)
Imports Matrix, Rcpp, stats, ggplot2, methods, cowplot, matrixStats
LinkingTo Rcpp, RcppArmadillo, BH
Suggests knitr, rmarkdown, BiocStyle, testthat
Depends On Me
Imports Me
Suggests Me
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