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For models that have only a single component, the tidy() and
glance() methods are identical. Please see the documentation for both
of those methods.
# S3 method for durbinWatsonTest
tidy(x, ...)# S3 method for durbinWatsonTest
glance(x, ...)
A tibble::tibble() with columns:
Alternative hypothesis (character).
Autocorrelation.
The two-sided p-value associated with the observed statistic.
Test statistic for Durbin-Watson test.
Always `Durbin-Watson Test`.
An object of class durbinWatsonTest created by a call to
car::durbinWatsonTest().
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ..., where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9, all computation will
proceed using conf.level = 0.95. Two exceptions here are:
tidy() methods will warn when supplied an exponentiate argument if
it will be ignored.
augment() methods will warn when supplied a newdata argument if it
will be ignored.
tidy(), glance(), car::durbinWatsonTest()
Other car tidiers:
leveneTest_tidiers
# load modeling library
library(car)
# fit model
dw <- durbinWatsonTest(lm(mpg ~ wt, data = mtcars))
# summarize model fit with tidiers
tidy(dw)
# same output for all durbinWatsonTests
glance(dw)
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