grpreg v3.3.0

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Regularization Paths for Regression Models with Grouped Covariates

Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.

Readme

GitHub version CRAN version downloads Travis build status codecov.io

Regularization Paths for Regression Models with Grouped Covariates

grpreg is an R package for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge. Utilities for carrying out cross-validation as well as post-fitting visualization, summarization, and prediction are also provided.

Install

  • To install the latest release version from CRAN: install.packages("grpreg")
  • To install the latest development version from GitHub: remotes::install_github("pbreheny/grpreg")

Get started

See the "getting started" vignette

Learn more

Follow the links under "Learn more" at the grpreg website

Details of the algorithms used

Functions in grpreg

Name Description
gBridge Fit a group bridge regression path
Lung VA lung cancer data set
logLik.grpreg logLik method for grpreg
Birthwt Risk Factors Associated with Low Infant Birth Weight
birthwt.grpreg Risk Factors Associated with Low Infant Birth Weight
AUC.cv.grpsurv Calculates AUC for cv.grpsurv objects
grpsurv Fit an group penalized survival model
grpreg Fit a group penalized regression path
cv.grpreg Cross-validation for grpreg/grpsurv
grpreg-package Regularization paths for regression models with grouped covariates
plot.grpsurv.func Plot survival curve for grpsurv model
summary.cv.grpreg Summarizing inferences based on cross-validation
predict.grpreg Model predictions based on a fitted grpreg object
select.grpreg Select an value of lambda along a grpreg path
predict.grpsurv Model predictions based on a fitted "grpsurv" object.
plot.grpreg Plot coefficients from a "grpreg" object
plot.cv.grpreg Plots the cross-validation curve from a cv.grpreg object
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Vignettes of grpreg

Name
web/models.rmd
web/penalties.rmd
getting-started.rmd
vignette.css
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Details

Date 2020-06-10
VignetteBuilder knitr
BugReports http://github.com/pbreheny/grpreg/issues
License GPL-3
URL http://pbreheny.github.io/grpreg, https://github.com/pbreheny/grpreg
LazyData TRUE
RoxygenNote 7.0.2
Encoding UTF-8
NeedsCompilation yes
Packaged 2020-06-10 17:45:26 UTC; pbreheny
Repository CRAN
Date/Publication 2020-06-10 18:20:02 UTC

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