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

Value

Returns an object of type "durbinWatsonTest".

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.

Author

John Fox jfox@mcmaster.ca

References

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

Examples

Run this code

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

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