# deviance.glmnet

##### Extract the deviance from a glmnet object

Compute the deviance sequence from the glmnet object

- Keywords
- models, regression

##### Usage

```
# S3 method for glmnet
deviance(object, ...)
```

##### Arguments

- object
fitted glmnet object

- …
additional print arguments

##### Details

A glmnet object has components `dev.ratio`

and `nulldev`

. The
former is the fraction of (null) deviance explained. The deviance
calculations incorporate weights if present in the model. The deviance is
defined to be 2*(loglike_sat - loglike), where loglike_sat is the
log-likelihood for the saturated model (a model with a free parameter per
observation). Null deviance is defined to be 2*(loglike_sat
-loglike(Null)); The NULL model refers to the intercept model, except for
the Cox, where it is the 0 model. Hence dev.ratio=1-deviance/nulldev, and
this `deviance`

method returns (1-dev.ratio)*nulldev.

##### Value

(1-dev.ratio)*nulldev

##### References

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

##### See Also

`glmnet`

, `predict`

, `print`

, and `coef`

methods.

##### Examples

```
# NOT RUN {
x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = glmnet(x, y)
deviance(fit1)
# }
```

*Documentation reproduced from package glmnet, version 3.0-2, License: GPL-2*