KOTORY: Robust Three-Group Tests for Heteroscedasticity in Linear
Regression
Tests for heteroscedasticity in the linear regression model that
sort the data by a regressor, split them into three equal parts and compare
the error scale of the parts. The ordinary least squares version 'kah3.test()'
refers the ratio of the largest to the smallest residual mean square to its
exact null distribution, Hartley's maximum F-ratio with three groups; the
robust version 'kah.robust.test()' replaces the mean squares by least trimmed
squares scales, so that outliers neither create nor hide heteroscedasticity,
and refers the ratio to a maximum F-ratio with simulated effective degrees of
freedom, to a Monte Carlo reference or to a residual bootstrap. The
distribution, density, quantile and random generation functions of the
maximum F-ratio are provided, together with 'run.all.het()', which runs the
proposed tests next to the Goldfeld-Quandt, Breusch-Pagan, White and robust
modified Goldfeld-Quandt tests in one call. For more details see Hartley
(1950) <doi:10.1093/biomet/37.3-4.308>, Goldfeld and Quandt (1965)
<doi:10.1080/01621459.1965.10480811> and Rousseeuw (1984)
<doi:10.1080/01621459.1984.10477105>.
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[aut],
Ebrahim Khaled Ebrahim