# plot.glmnet

0th

Percentile

##### plot coefficients from a "glmnet" object

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

Keywords
models, regression
##### Usage
# S3 method for glmnet
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE, ...)
# S3 method for multnet
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)
# S3 method for mrelnet
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)
##### Arguments
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

##### Details

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

##### References

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

glmnet, and print, predict and coef methods.

• plot.glmnet
• plot.multnet
• plot.mrelnet
##### Examples
# NOT RUN {
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)
# }

Documentation reproduced from package glmnet, version 2.0-10, License: GPL-2

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