check_autocorrelation: Check model for independence of residuals.

In performance: Assessment of Regression Models Performance

Check model for independence of residuals.

Description

Check model for independence of residuals, i.e. for autocorrelation of error terms.

Usage

check_autocorrelation(x, ...)

## Default S3 method:
check_autocorrelation(x, nsim = 1000, ...)

Arguments

x	A model object.
...	Currently not used.
nsim	Number of simulations for the Durbin-Watson-Test.

Details

Performs a Durbin-Watson-Test to check for autocorrelated residuals. In case of autocorrelation, robust standard errors return more accurate results for the estimates, or maybe a mixed model with error term for the cluster groups should be used.

Value

Invisibly returns the p-value of the test statistics. A p-value < 0.05 indicates autocorrelated residuals.

See Also

Other functions to check model assumptions and and assess model quality: check_collinearity(), check_convergence(), check_heteroscedasticity(), check_homogeneity(), check_model(), check_outliers(), check_overdispersion(), check_predictions(), check_singularity(), check_zeroinflation()

Examples

m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
check_autocorrelation(m)

performance documentation built on Nov. 2, 2023, 5:48 p.m.