Other packages > Find by keyword >

xtune  

Regularized Regression with Feature-Specific Penalties Integrating External Information
View on CRAN: Click here


Download and install xtune package within the R console
Install from CRAN:
install.packages("xtune")

Install from Github:
library("remotes")
install_github("cran/xtune")

Install by package version:
library("remotes")
install_version("xtune", "2.0.0")



Attach the package and use:
library("xtune")
Maintained by
Jingxuan He
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-24
Latest Update: 2025-09-03
Description:
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.
How to cite:
Jingxuan He (2019). xtune: Regularized Regression with Feature-Specific Penalties Integrating External Information. R package version 2.0.0, https://cran.r-project.org/web/packages/xtune. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:56), 0.1.0 (2019-05-24 11:00), 2.0.0 (2023-06-19 00:40)
Other packages that cited xtune R package
View xtune citation profile
Other R packages that xtune depends, imports, suggests or enhances
Complete documentation for xtune
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

gemlog  
File Conversion for "Gem Infrasound Logger"
Reads data files from the 'Gem infrasound logger' for analysis and converts to segy format (which is ...
Download / Learn more Package Citations See dependency  
forecastHybrid  
Convenient Functions for Ensemble Time Series Forecasts
Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. ...
Download / Learn more Package Citations See dependency  
magicfor  
Magic Functions to Obtain Results from for Loops
Magic functions to obtain results from for loops. ...
Download / Learn more Package Citations See dependency  
givitiR  
The GiViTI Calibration Test and Belt
Functions to assess the calibration of logistic regression models with the GiViTI (Gruppo Italiano p ...
Download / Learn more Package Citations See dependency  
FDRsampsize  
Compute Sample Size that Meets Requirements for Average Power and FDR
Defines a collection of functions to compute average power and sample size for studies that use the ...
Download / Learn more Package Citations See dependency  
climwin  
Climate Window Analysis
Contains functions to detect and visualise periods of climate sensitivity (climate windows) for a g ...
Download / Learn more Package Citations See dependency  

29,080

R Packages

247,686

Dependencies

77,281

Author Associations

29,081

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA