# Cook's Distances

##### Cook's Distances for Linear and Generalized Linear Models

This function now simply calls `cooks.distance`

in the `base`

package.

- Keywords
- models, regression

##### Usage

`cookd(model, ...)`

##### Arguments

- model
`lm`

or`glm`

model object.- ...
- other arguments to be passed to
`cooks.distance`

.

##### Details

Cook's distances for generalized linear
models are approximations, as described in Williams (1987) (except that the Cook's distances are
scaled as *F* rather than as chi-square values).
This function is retained primarily for consistency with *An R and S-PLUS Companion
to Applied Regression.* Other deletion diagnostics formerly in the `car`

package have
been rewritten and moved to the `base`

package; these include `influence`

,
`rstudent`

, `hatvalues`

, `dfbeta`

, and `dfbetas`

.

##### Value

`cookd`

returns a vector with one entry for each observation.

##### References

Cook, R. D. and Weisberg, S. (1984)
*Residuals and Influence in Regression.* Wiley.
Fox, J. (1997)
*Applied Regression, Linear Models, and Related Methods.* Sage.
Williams, D. A. (1987)
Generalized linear model diagnostics using the deviance and single
case deletions. *Applied Statistics* **36**, 181--191.

##### See Also

##### Examples

```
data(Duncan)
attach(Duncan)
mod <- lm(prestige ~ income + education)
plot(cookd(mod))
```

*Documentation reproduced from package car, version 1.0-18, License: GPL version 2 or newer*