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 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, ...)

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 an object of type `"durbinWatsonTest"`

.

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

# NOT RUN { durbinWatsonTest(lm(fconvict ~ tfr + partic + degrees + mconvict, data=Hartnagel)) # }