plot.glmnet: plot coefficients from a "glmnet" object
In jeffwong/glmnet: Lasso and elastic-net regularized generalized linear models

Description Usage Arguments Details Author(s) References See Also Examples

Produces a coefficient profile plot of the coefficient paths for a fitted "glmnet" object.

## S3 method for class 'glmnet'
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE, ...)
## S3 method for class 'multnet'
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)
## S3 method for class 'mrelnet'
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)

`x`	fitted `"glmnet"` model
`xvar`	What is on the X-axis. `"norm"` plots against the L1-norm of the coefficients, `"lambda"` against the log-lambda sequence, and `"dev"` against the percent deviance explained.
`label`	If `TRUE`, label the curves with variable sequence numbers.
`type.coef`	If `type.coef="2norm"` then a single curve per variable, else if `type.coef="coef"`, a coefficient plot per response
`...`	Other graphical parameters to plot

A coefficient profile plot is produced. If x is a multinomial model, a coefficient plot is produced for each class.

Jerome Friedman, Trevor Hastie and Rob Tibshirani
Maintainer: Trevor Hastie <hastie@stanford.edu>

Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent

glmnet, and print, predict and coef methods.

x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
g2=sample(1:2,100,replace=TRUE)
g4=sample(1:4,100,replace=TRUE)
fit1=glmnet(x,y)
plot(fit1)
plot(fit1,xvar="lambda",label=TRUE)
fit3=glmnet(x,g4,family="multinomial")
plot(fit3,pch=19)