print.grpnet | R Documentation |
Print a summary of the grpnet path at each step along the path.
## S3 method for class 'grpnet'
print(x, digits = max(3, getOption("digits") - 3), ...)
x |
fitted grpnet object |
digits |
significant digits in printout |
... |
additional print arguments |
The call that produced the object x
is printed, followed by a
three-column matrix with columns Df
, %Dev
and Lambda
.
The Df
column is the number of nonzero coefficients (Df is a
reasonable name only for lasso fits). %Dev
is the percent deviance
explained (relative to the null deviance).
The matrix above is silently returned
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")}.
grpnet
, predict
, plot
and coef
methods.
x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = grpnet(x, glm.gaussian(y))
print(fit1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.