rqPen: rqPen: A package for estimating quantile regression models...
In rqPen: Penalized Quantile Regression
rqPen R Documentation
rqPen: A package for estimating quantile regression models using penalized objective functions.
Description
The package estimates a quantile regression model using LASSO, Adaptive LASSO, SCAD, MCP, elastic net,
and their group counterparts, with the exception of elastic net for which there is no group penalty implementation.
rqPen functions
The most important functions are rq.pen(), rq.group.pen(), rq.pen.cv() and rq.group.pen.cv(). These functions
fit quantile regression models with individual or group penalties. The cv functions automate the cross-validation process for selection of tuning parameters.
rqPen documentation built on Aug. 25, 2023, 1:07 a.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| rqPen | R Documentation |
rqPen: A package for estimating quantile regression models using penalized objective functions.
Description
The package estimates a quantile regression model using LASSO, Adaptive LASSO, SCAD, MCP, elastic net, and their group counterparts, with the exception of elastic net for which there is no group penalty implementation.
rqPen functions
The most important functions are rq.pen(), rq.group.pen(), rq.pen.cv() and rq.group.pen.cv(). These functions fit quantile regression models with individual or group penalties. The cv functions automate the cross-validation process for selection of tuning parameters.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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