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

object.

```
# S3 method for glmnet
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE, ...)
# S3 method for mrelnet
plot(
x,
xvar = c("norm", "lambda", "dev"),
label = FALSE,
type.coef = c("coef", "2norm"),
...
)
# S3 method for multnet
plot(
x,
xvar = c("norm", "lambda", "dev"),
label = FALSE,
type.coef = c("coef", "2norm"),
...
)
# S3 method for relaxed
plot(x, xvar = c("lambda", "dev"), label = FALSE, gamma = 1, ...)
```

## 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.

- ...
Other graphical parameters to plot

- type.coef
If `type.coef="2norm"`

then a single curve per
variable, else if `type.coef="coef"`

, a coefficient plot per response

- gamma
Value of the mixing parameter for a "relaxed" fit

## 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.

## Author

Jerome Friedman, Trevor Hastie and Rob Tibshirani

Maintainer:
Trevor Hastie hastie@stanford.edu

## 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)
```