View source: R/harrison_mccabe.R
harrison_mccabe | R Documentation |
This function implements the method of \insertCiteHarrison79;textualskedastic for testing for heteroskedasticity in a linear regression model.
harrison_mccabe( mainlm, deflator = NA, m = 0.5, alternative = c("less", "greater", "two.sided"), twosidedmethod = c("doubled", "kulinskaya"), qfmethod = "imhof", statonly = FALSE )
mainlm |
Either an object of |
deflator |
Either a character specifying a column name from the
design matrix of |
m |
Either a |
alternative |
A character specifying the form of alternative
hypothesis. If it is suspected that the error variance is positively
associated with the deflator variable, |
twosidedmethod |
A character indicating the method to be used to compute
two-sided p-values for the parametric test when |
qfmethod |
A character, either |
statonly |
A logical. If |
The test assumes that heteroskedasticity, if present, is monotonically related to one of the explanatory variables (known as the deflator). The OLS residuals e are placed in increasing order of the deflator variable and we let A be an n\times n selector matrix whose first m diagonal elements are 1 and all other elements are 0. The alternative hypothesis posits that the error variance changes around index m. Under the null hypothesis of homoskedasticity, the ratio of quadratic forms Q=\frac{e' A e}{e'e} should be close to \frac{m}{n}. Since the test statistic Q is a ratio of quadratic forms in the errors, the Imhof algorithm is used to compute p-values (with normality of errors assumed).
An object of class
"htest"
. If object is
not assigned, its attributes are displayed in the console as a
tibble
using tidy
.
lmtest::hmctest
, another
implementation of the Harrison-McCabe Test. Note that the p-values
from that function are simulated rather than computed from the
distribution of a ratio of quadratic forms in normal random vectors.
mtcars_lm <- lm(mpg ~ wt + qsec + am, data = mtcars) harrison_mccabe(mtcars_lm, deflator = "qsec")
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