cv_plots

Plots of cross validation results as a function of lambda.

internal

Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.

Ben Sherwood

rqPen

Penalized Quantile Regression

Shaobo Li

Adam Maidman

cv_plots function

<dl><dt>model</dt>
<dd>A cv.rq.pen() object.</dd>
<dt>logLambda</dt>
<dd>Whether lambda values should be logged or not.</dd>
<dt>loi</dt>
<dd>Lambda indexes of interest, if null all lambda values will be used.</dd>
<dt>...</dt>
<dd>Additional parameters sent to plot function.</dd></dl>

Arguments

Ben Sherwood, <a href="/link/ben.sherwood%40ku.edu?package=rqPen&version=4.1.3" data-mini-rdoc="rqPen::ben.sherwood@ku.edu">ben.sherwood@ku.edu</a>

Author

Plots of cross validation results as a function of lambda. — cv_plots

<dl>

<dt>model</dt>
<dd>A cv.rq.pen() object.</dd>


<dt>logLambda</dt>
<dd>Whether lambda values should be logged or not.</dd>


<dt>loi</dt>
<dd>Lambda indexes of interest, if null all lambda values will be used.</dd>


<dt>...</dt>
<dd>Additional parameters sent to plot function.</dd>

</dl>

Ben Sherwood, <a href='mailto:ben.sherwood@ku.edu'>ben.sherwood@ku.edu</a>

cv_plots: Plots of cross validation results as a function of lambda.

Description

Usage

Value

Arguments

Author