plot.grpnet | R Documentation |
Produces a coefficient profile plot of the coefficient paths for a fitted
"grpnet"
object.
## S3 method for class 'grpnet'
plot(x, sign.lambda = -1, glm.name = TRUE, ...)
x |
fitted |
sign.lambda |
This determines whether we plot against |
glm.name |
This is a logical (default |
... |
Other graphical parameters to plot |
A coefficient profile plot is produced. If x
is a multinomial or multigaussian model,
the 2norm of the vector of coefficients is plotted.
James Yang, Trevor Hastie, and Balasubramanian Narasimhan
Maintainer: Trevor Hastie hastie@stanford.edu
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
, and print
, and coef
methods, and
cv.grpnet
.
x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
fit1=grpnet(x,glm.gaussian(y))
plot(fit1)
g4=diag(4)[sample(1:4,100,replace=TRUE),]
fit2=grpnet(x,glm.multinomial(g4))
plot(fit2,lwd=3)
fit3=grpnet(x,glm.gaussian(y),groups=c(1,5,9,13,17))
plot(fit3)
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