durbinWatsonTest function

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.

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.

Returns

Returns an object of type "durbinWatsonTest".

Note

p-values are available only from the lm method.

References

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

Author(s)

John Fox jfox@mcmaster.ca

Examples

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