# durbinWatsonTest

From car v2.0-20
by John Fox

##### Durbin-Watson Test for Autocorrelated Errors

Computes residual autocorrelations and generalized Durbin-Watson
statistics and their bootstrapped p-values. `dwt`

is an
abbreviation for `durbinWatsonTest`

.

- Keywords
- regression, ts

##### Usage

```
durbinWatsonTest(model, ...)
dwt(...)
## S3 method for class 'lm':
durbinWatsonTest(model, max.lag=1, simulate=TRUE, reps=1000,
method=c("resample","normal"),
alternative=c("two.sided", "positive", "negative"), ...)
## S3 method for class 'default':
durbinWatsonTest(model, max.lag=1, ...)
## S3 method for class 'durbinWatsonTest':
print(x, ...)
```

##### Arguments

- model
- a linear-model object, or a vector of residuals from a linear model.
- max.lag
- maximum lag to which to compute residual autocorrelations and Durbin-Watson statistics.
- simulate
- if
`TRUE`

p-values will be estimated by bootstrapping. - reps
- number of bootstrap replications.
- method
- bootstrap method:
`"resample"`

to resample from the observed residuals;`"normal"`

to sample normally distributed errors with 0 mean and standard deviation equal to the standard error of the regression. - alternative
- sign of autocorrelation in alternative hypothesis; specify
only if
`max.lag = 1`

; if`max.lag > 1`

, then`alternative`

is taken to be`"two.sided"`

. - ...
- arguments to be passed down.
- x
`durbinWatsonTest`

object.

##### Value

- Returns an object of type
`"durbinWatsonTest"`

.

##### Note

p-values are available only from the `lm`

method.

##### References

Fox, J. (2008)
*Applied Regression Analysis and Generalized Linear Models*, Second Edition. Sage.

##### Examples

`durbinWatsonTest(lm(fconvict ~ tfr + partic + degrees + mconvict, data=Hartnagel))`

*Documentation reproduced from package car, version 2.0-20, License: GPL (>= 2)*

### Community examples

Looks like there are no examples yet.