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rqPen (version 2.3)

Penalized Quantile Regression

Description

Performs penalized quantile regression for LASSO, SCAD and MCP functions including group penalties. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC.

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Version

Install

install.packages('rqPen')

Monthly Downloads

806

Version

2.3

License

MIT + file LICENSE

Maintainer

Ben Sherwood

Last Published

March 22nd, 2022

Functions in rqPen (2.3)

coef.cv.rq.pen

Penalized Quantile Regression Coefficients
beta_plots

Plots of Betas
QICD.nonpen

Penalized Quantile Regression with some nonpenalized coefficients with QICD Algorithm
coef.cv.rq.group.pen

Group Penalized Quantile Regression Coefficients
QICD

Penalized Quantile Regression with QICD Algorithm
QICD.group

Group Penalized Quantile Regression with QICD Algorithm
QICD.master

Master QICD Function for Regular QICD, group QICD, and Partially Penalized QICD with Multiple Lambdas
check

Quantile check function
LASSO.fit

LASSO Penalized Quantile Regression
LASSO.fit.nonpen

LASSO Penalized Quantile Regression with some nonpenalized coefficients
mcp

MCP
rqPen-package

Penalized quantile regression for LASSO, SCAD, and MCP penalty functions including group penalties
nonzero

Nonzero
groupMultLambda

Quantile Regression with Group Penalty for multiple lambdas
model_eval

Model Evaluation
get_coef_pen

Returns the coefficient part of the penalized objective function
rq.nc.fit

Non-convex penalized quantile regression
cv_plots

Plots of Cross-validation results
predict.rq.pen

Prediction from a quantile regression penalized model
getRho

Objective Function Value
rq.group.fit

Quantile Regresion with Group Penalty
print.cv.rq.pen

Print cv.rq.pen object
cv.rq.group.pen

Cross Validated quantile regression with group penalty
cv.rq.pen

Cross Validated quantile regression
group_derivs

Derivative of a group penalty
nonzero.cv.rq.group.pen

Nonzero
mcp_deriv

MCP Derivative
print.rq.pen

Print rq.pen object
lasso

Lasso
qaSIS

Quantile Adaptive Sure Independence Screening
scad

scad
scad_deriv

SCAD Derivative
rq.group.lin.prog

Quantile Regresion with Group Penalty using linear programming algorithm
pos_part

Positive part
plot.cv.rq.group.pen

Plot cv.rq.group.pen
predict.cv.rq.pen

Prediction from a cv quantile regression penalized model
rq.lasso.fit

Quantile Regression with LASSO penalty
transform_coefs

Transform coefficients back to original scale
square

Square function
qbic

Quantile Regresion BIC
randomly_assign

Randomly Assign
rq.lasso.fit.mult

Fit Quantile Regression model for varying quantiles with LASSO penalty