Package: xtune 2.0.0

Jingxuan He

xtune: Regularized Regression with Feature-Specific Penalties Integrating External Information

Extends standard penalized regression (Lasso, Ridge, and Elastic-net) to allow feature-specific shrinkage based on external information with the goal of achieving a better prediction accuracy and variable selection. Examples of external information include the grouping of predictors, prior knowledge of biological importance, external p-values, function annotations, etc. The choice of multiple tuning parameters is done using an Empirical Bayes approach. A majorization-minimization algorithm is employed for implementation.

Authors:Jingxuan He [aut, cre], Chubing Zeng [aut]

xtune_2.0.0.tar.gz
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xtune_2.0.0.tgz(r-4.4-any)xtune_2.0.0.tgz(r-4.3-any)
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xtune_2.0.0.tgz(r-4.4-emscripten)xtune_2.0.0.tgz(r-4.3-emscripten)
xtune.pdf |xtune.html
xtune/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/jingxuanh/xtune/issues

Datasets:
  • diet - Simulated diet data to predict weight loss
  • example - An simulated example dataset
  • example.multiclass - Simulated data with multi-categorical outcome
  • gene - Simulated gene data to predict weight loss

On CRAN:

3.85 score 14 scripts 158 downloads 1 mentions 7 exports 19 dependencies

Last updated 1 years agofrom:33d88886b6. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 11 2024
R-4.5-winNOTEOct 11 2024
R-4.5-linuxNOTEOct 11 2024
R-4.4-winNOTEOct 11 2024
R-4.4-macNOTEOct 11 2024
R-4.3-winNOTEOct 11 2024
R-4.3-macNOTEOct 11 2024

Exports:coef_xtuneestimateVariancemisclassificationmsepredict_xtunextunextune.control

Dependencies:adaptMCMCcodacodetoolscrayonforeachglmnetintervalsiteratorslatticelbfgsMASSMatrixramcmcRcppRcppArmadilloRcppEigenselectiveInferenceshapesurvival

Getting started with xtune

Rendered fromTutorials_for_xtune.Rmdusingknitr::rmarkdownon Oct 11 2024.

Last update: 2023-06-17
Started: 2023-06-15