rqPen4.2 package

Penalized Quantile Regression

beta_plots

Plots of coefficients by lambda for cv.rq.group.pen and cv.rq.pen

bytau.plot

Plot of how coefficients change with tau

bytau.plot.rq.pen.seq.cv

Plot of coefficients varying by quantiles for rq.pen.seq.cv object

bytau.plot.rq.pen.seq

Plot of how coefficients change with tau.

coef.cv.rq.group.pen

Coefficients from a cv.rq.group.pen object

coef.cv.rq.pen

Returns Coefficients of a cv.rq.pen object

coef.rq.pen.seq.cv

Returns coefficients from a rq.pen.seq.cv object.

coef.rq.pen.seq

Returns coefficients of a rq.pen.seq object

cv_plots

Plots of cross validation results as a function of lambda.

cv.rq.group.pen

Old cross validation function for group penalty

plot.cv.rq.group.pen

Cross validation plot for cv.rq.group.pen object

plot.rq.pen.seq.cv

Plots cross validation results from a rq.pen.seq.cv object

plot.rq.pen.seq

Plot of coefficients of rq.pen.seq object as a function of lambda

predict.cv.rq.pen

Prediction for a cv.rq.pen object

predict.qic.select

Predictions from a qic.select object

predict.rq.pen

Prediction for a rq.pen object

predict.rq.pen.seq.cv

Predictions from rq.pen.seq.cv object

predict.rq.pen.seq

Predictions from rq.pen.seq object

print.qic.select

Print a qic.select object

print.rq.pen.seq.cv

Prints a rq.pen.seq.cv object

print.rq.pen.seq

Print a rq.pen.seq object

qic

Calculate information criterion for penalized quantile regression mode...

qic.select

Select tuning parameters using IC

qic.select.rq.pen.seq.cv

Select tuning parameters using IC

qic.select.rq.pen.seq

Select tuning parameters using IC

rq.gq.pen.cv

Title Cross validation for consistent variable selection across multip...

rq.gq.pen

Title Quantile regression estimation and consistent variable selection...

rq.group.fit

Estimates a quantile regression model with a group penalized objective...

rq.group.pen.cv

Performs cross validation for a group penalty.

rq.group.pen

Fits quantile regression models using a group penalized objective func...

rq.lasso.fit

Estimates a quantile regression model with a lasso penalized quanitle ...

rq.nc.fit

Non-convex penalized quantile regression

rq.pen.cv

Does k-folds cross validation for rq.pen. If multiple values of a are ...

rq.pen

Fit a quantile regression model using a penalized quantile loss functi...

rqPen

rqPen: A package for estimating quantile regression models using penal...

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 article in the R Journal.