Package: graper 1.21.0
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:
graper_1.21.0.tar.gz
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graper.pdf |graper.html✨
graper/json (API)
NEWS
| # Install 'graper' in R: |
| install.packages('graper', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:graper-1.21.0(bioc 3.20)graper-1.20.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:7b45fcc7a5
Exports:getPIPsgrapermakeExampleDatamakeExampleDataWithUnequalGroupsplotELBOplotGroupPenaltiesplotPosterior
Dependencies:BHclicolorspacecowplotfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr
Vignette illustrating the use of graper in linear regression
Rendered fromexample_linear.Rmdusingknitr::rmarkdownon Jun 18 2024.Last update: 2019-01-29
Started: 2018-07-13
Vignette illustrating the use of graper in logistic regression
Rendered fromexample_logistic.Rmdusingknitr::rmarkdownon Jun 18 2024.Last update: 2019-06-20
Started: 2018-10-01
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Get estimated coefficients from a graper object | coef.graper |
| Get posterior inclusion probabilities per feature | getPIPs |
| Fit a regression model with graper | graper |
| Simulate example data from the graper model | makeExampleData |
| Simulate example data from the graper model with groups of unequal size | makeExampleDataWithUnequalGroups |
| Plot evidence lower bound | plotELBO |
| Plot group-wise penalties | plotGroupPenalties |
| Plot posterior distributions | plotPosterior |
| Predict response on new data | predict.graper |
| Print a graper object | print.graper |
