R: Durbin-Watson Test for Autocorrelated Errors

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

### Examples

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

[Package car version 2.1-4 Index]