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elasticnet (version 1.02)

Elastic Net Regularization and Variable Selection

Description

Efficient procedures for fitting an entire elastic net sequence. The elastic net methodology is described in the paper below. The package also implements the sparse PCA algorithm based on the elastic net/lasso.

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Version

Install

install.packages('elasticnet')

Monthly Downloads

2,336

Version

1.02

License

GPL version 2 or newer

Maintainer

Hui Zou

Last Published

May 16th, 2020

Functions in elasticnet (1.02)

predict.enet

Make predictions or extract coefficients from a fitted elastic net model
print.spca

Print method for spca objects
print.enet

Print method for enet objects
enet

Fits Elastic Net regression models
pitprops

Pitprops correlation data
print.arrayspc

Print method for arrayspc objects
plot.enet

Plot method for enet objects
cv.enet

Computes K-fold cross-validated error curve for elastic net
spca

Sparse Principal Components Analysis
diabetes

Blood and other measurements in diabetics
arrayspc

Sparse PCs of Microarrays
elasticnet-internal

Internal elasticnet functions