plot.glmnet {glmnet} | R Documentation |

## plot coefficients from a "glmnet" object

### Description

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

object.

### Usage

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

### Arguments

`x` |
fitted |

`xvar` |
What is on the X-axis. |

`label` |
If |

`...` |
Other graphical parameters to plot |

`type.coef` |
If |

`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.

### Author(s)

Jerome Friedman, Trevor Hastie and Rob Tibshirani

Maintainer:
Trevor Hastie hastie@stanford.edu

### 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)
```

*glmnet*version 4.1-8 Index]