print.cpernet: Print a cpernet object

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

Print a cpernet object

Description

Print a summary of the cpernet path at each step along the path.

Usage

## S3 method for class 'cpernet'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x	fitted cpernet object.
digits	significant digits in the output.
...	additional print arguments.

Details

The call that produced the cpernet object is printed, followed by a three-column matrix with columns Df1, Df2 and Lambda. The Df1 and Df2 columns are the number of nonzero mean and scale coefficients respectively.

Value

a three-column matrix, the first two columns are the number of nonzero mean and scale coefficients respectively and the third column is Lambda.

Author(s)

Yuwen Gu and Hui Zou

Maintainer: Yuwen Gu <[e-mail]>

Examples

set.seed(1)
n <- 100
p <- 400
x <- matrix(rnorm(n * p), n, p)
y <- rnorm(n)
tau <- 0.30
pf <- abs(rnorm(p))
pf2 <- abs(rnorm(p))
w <- 2.0
lambda2 <- 1
m2 <- cpernet(y = y, x = x, w = w, tau = tau, eps = 1e-8,
              pf.mean = pf, pf.scale = pf2,
              standardize = FALSE, lambda2 = lambda2)
print(m2)

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