# plot.glmnet

From glmnet v1.9-3
by Trevor Hastie

##### 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 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"), ...)
```

##### 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*

##### See Also

`glmnet`

, and `print`

, `predict`

and `coef`

methods.

##### Examples

```
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 1.9-3, License: GPL-2*

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