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

In SALES: 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

Plot the cross-validated curve produced by cv.ernet

Description

Plots the cross-validated curve, and upper and lower standard deviation curves, as a function of the lambda values used. This function is modified based on the plot.cv.glmnet function from the glmnet package.

Usage

## S3 method for class 'cv.ernet'
plot(x, sign.lambda = 1, ...)

Arguments

x	fitted cv.ernet object
sign.lambda	either plot against log(lambda) (default) or its negative if sign.lambda=-1.
...	other graphical parameters to plot

Details

A plot is produced.

Author(s)

Yuwen Gu and Hui Zou

Maintainer: Yuwen Gu <[e-mail]>

See Also

plot.ernet

Examples

set.seed(1)
n <- 100
p <- 400
x <- matrix(rnorm(n * p), n, p)
y <- rnorm(n)
tau <- 0.90
pf <- abs(rnorm(p))
pf2 <- abs(rnorm(p))
lambda2 <- 1
m1.cv <- cv.ernet(y = y, x = x, tau = tau, eps = 1e-8, pf = pf,
                  pf2 = pf2, standardize = FALSE, intercept = FALSE,
                  lambda2 = lambda2)
plot(m1.cv)

SALES documentation built on Aug. 16, 2022, 1:05 a.m.