print.cv.grpnet: print a cross-validated grpnet object

In adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

print a cross-validated grpnet object

Description

Print a summary of the results of cross-validation for a grpnet model.

Usage

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

Arguments

x	fitted 'cv.grpnet' object
digits	significant digits in printout
...	additional print arguments

Author(s)

James Yang, Trevor Hastie, and Balasubramanian Narasimhan
Maintainer: Trevor Hastie [e-mail]

References

Yang, James and Hastie, Trevor. (2024) A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent. arXiv \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2405.08631")}.

See Also

grpnet, predict and coef methods.

Examples

x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = cv.grpnet(x, glm.gaussian(y))
print(fit1)

adelie documentation built on Sept. 11, 2024, 6:36 p.m.