Penalized Quantile Regression


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Documentation for package ‘rqPen’ version 4.1.1

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rqPen-package rqPen: A package for estimating quantile regression models using penalized objective functions.
bytau.plot Plot of how coefficients change with tau
bytau.plot.rq.pen.seq 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
coef.rq.pen.seq Returns coefficients of a rq.pen.seq object
coef.rq.pen.seq.cv Returns coefficients from a rq.pen.seq.cv object.
plot.rq.pen.seq Plot of coefficients of rq.pen.seq object as a function of lambda
plot.rq.pen.seq.cv Plots cross validation results from a rq.pen.seq.cv object
predict.qic.select Predictions from a qic.select object
predict.rq.pen.seq Predictions from rq.pen.seq object
predict.rq.pen.seq.cv Predictions from rq.pen.seq.cv object
print.qic.select Print a qic.select object
print.rq.pen.seq Print a rq.pen.seq object
print.rq.pen.seq.cv Prints a rq.pen.seq.cv object
qic.select Select tuning parameters using IC
qic.select.rq.pen.seq Select tuning parameters using IC
qic.select.rq.pen.seq.cv Select tuning parameters using IC
rq.gq.pen Title Quantile regression estimation and consistent variable selection across multiple quantiles
rq.gq.pen.cv Title Cross validation for consistent variable selection across multiple quantiles.
rq.group.pen Fits quantile regression models using a group penalized objective function.
rq.group.pen.cv Performs cross validation for a group penalty.
rq.pen Fit a quantile regression model using a penalized quantile loss function.
rq.pen.cv Does k-folds cross validation for rq.pen. If multiple values of a are specified then does a grid based search for best value of lambda and a.
rqPen rqPen: A package for estimating quantile regression models using penalized objective functions.