Package: graper 1.23.0

Britta Velten

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

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.

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

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NEWS

# Install 'graper' in R:
install.packages('graper', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On BioConductor:graper-1.23.0(bioc 3.21)graper-1.22.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

regressionbayesianclassification

4.41 score 13 scripts 147 downloads 1 mentions 7 exports 33 dependencies

Last updated 23 days agofrom:91803f0184. Checks:OK: 1 NOTE: 4 WARNING: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-win-x86_64NOTENov 19 2024
R-4.5-linux-x86_64NOTENov 19 2024
R-4.4-win-x86_64NOTENov 19 2024
R-4.4-mac-x86_64WARNINGNov 19 2024
R-4.4-mac-aarch64WARNINGNov 19 2024
R-4.3-win-x86_64NOTENov 19 2024
R-4.3-mac-x86_64WARNINGNov 19 2024
R-4.3-mac-aarch64WARNINGNov 19 2024

Exports:getPIPsgrapermakeExampleDatamakeExampleDataWithUnequalGroupsplotELBOplotGroupPenaltiesplotPosterior

Dependencies:BHclicolorspacecowplotfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr

Vignette illustrating the use of graper in linear regression

Rendered fromexample_linear.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2019-01-29
Started: 2018-07-13

Vignette illustrating the use of graper in logistic regression

Rendered fromexample_logistic.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2019-06-20
Started: 2018-10-01