Learn R Programming

SALES (version 1.0.2)

The (Adaptive) Elastic Net and Lasso Penalized Sparse Asymmetric Least Squares (SALES) and Coupled Sparse Asymmetric Least Squares (COSALES) using Coordinate Descent and Proximal Gradient Algorithms

Description

A coordinate descent algorithm for computing the solution paths of the sparse and coupled sparse asymmetric least squares, including the (adaptive) elastic net and Lasso penalized SALES and COSALES regressions.

Copy Link

Version

Install

install.packages('SALES')

Monthly Downloads

170

Version

1.0.2

License

GPL (>= 2)

Issues

0

Pull Requests

0

Stars

2

Forks

1

Maintainer

Yuwen Gu

Last Published

August 15th, 2022

Functions in SALES (1.0.2)

coef.ernet

Get coefficients from an ernet object
predict.cv.cpernet

Make predictions from a cv.cpernet object
predict.cpernet

Make predictions from a cpernet object
cv.ernet

Cross-validation for ernet
cv.cpernet

Cross-validation for cpernet
ernet

Regularization paths for the sparse asymmetric least squares (SALES) regression (or the sparse expectile regression)
coef.cv.cpernet

Get coefficients from a cv.cpernet object
print.ernet

Print an ernet object
plot.cpernet

Plot coefficients from a cpernet object
print.cpernet

Print a cpernet object
predict.cv.ernet

Make predictions from a cv.ernet object
coef.cv.ernet

Get coefficients from a cv.ernet object
coef

Extract Model Coefficients
predict.ernet

Make predictions from an ernet object
coef.cpernet

Get coefficients from a cpernet object
plot.ernet

Plot coefficients from an ernet object
predict

Model predictions
cpernet

Regularization paths for the coupled sparse asymmetric least squares (COSALES) regression (or the coupled sparse expectile regression)
plot.cv.cpernet

Plot the cross-validated curve produced by cv.cpernet
plot.cv.ernet

Plot the cross-validated curve produced by cv.ernet