durbinWatsonTest {car} R Documentation

## Durbin-Watson Test for Autocorrelated Errors

### Description

Computes residual autocorrelations and generalized Durbin-Watson statistics and their bootstrapped p-values. `dwt` is an abbreviation for `durbinWatsonTest`.

### 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"), ...)

## Default S3 method:
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.

### Author(s)

John Fox jfox@mcmaster.ca

### References

Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.

### Examples

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

[Package car version 3.0-11 Index]