R: 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

# 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

## Documentation for package ‘SALES’ version 1.0.2

- DESCRIPTION file

## Help Pages

coef | Extract Model Coefficients
coef.alspath | Get coefficients from an ernet object
coef.cpalspath | Get coefficients from a cpernet object
coef.cpernet | Get coefficients from a cpernet object
coef.cv.cpernet | Get coefficients from a cv.cpernet object
coef.cv.ernet | Get coefficients from a cv.ernet object
coef.ernet | Get coefficients from an ernet object
cpernet | Regularization paths for the coupled sparse asymmetric least squares (COSALES) regression (or the coupled sparse expectile regression)
cv.cpernet | Cross-validation for cpernet
cv.ernet | Cross-validation for ernet
ernet | Regularization paths for the sparse asymmetric least squares (SALES) regression (or the sparse expectile regression)
plot.cpernet | Plot coefficients from a cpernet object
plot.cv.cpernet | Plot the cross-validated curve produced by cv.cpernet
plot.cv.ernet | Plot the cross-validated curve produced by cv.ernet
plot.ernet | Plot coefficients from an ernet object
predict | Model predictions
predict.alspath | Make predictions from an ernet object
predict.cpalspath | Make predictions from a cpernet object
predict.cpernet | Make predictions from a cpernet object
predict.cv.cpernet | Make predictions from a cv.cpernet object
predict.cv.ernet | Make predictions from a cv.ernet object
predict.ernet | Make predictions from an ernet object
print.cpernet | Print a cpernet object
print.ernet | Print an ernet object