This function implements the two methods of Yuce08;textualskedastic for testing for heteroskedasticity in a linear regression model.
yuce(mainlm, method = c("A", "B"), statonly = FALSE)An object of class
"htest". If object is
not assigned, its attributes are displayed in the console as a
Either an object of class "lm"
(e.g., generated by lm), or
a list of two objects: a response vector and a design matrix. The objects
are assumed to be in that order, unless they are given the names
"X" and "y" to distinguish them. The design matrix passed
in a list must begin with a column of ones if an intercept is to be
included in the linear model. The design matrix passed in a list should
not contain factors, as all columns are treated 'as is'. For tests that
use ordinary least squares residuals, one can also pass a vector of
residuals in the list, which should either be the third object or be
named "e".
A character indicating which of the two tests presented in
Yuce08;textualskedastic should be implemented. Possible
values are "A" (the chi-squared test) and
"B" (the \(t\)-test). Partial matching is used and the argument
is not case-sensitive.
A logical. If TRUE, only the test statistic value
is returned, instead of an object of class
"htest". Defaults to FALSE.
These two tests are straightforward to implement; in both cases the test statistic is a function only of the residuals of the linear regression model. The first test statistic has an asymptotic chi-squared distribution and the second has an asymptotic \(t\)-distribution. In both cases the degrees of freedom are \(n-p\). The chi-squared test is right-tailed whereas the \(t\)-test is two-tailed.
mtcars_lm <- lm(mpg ~ wt + qsec + am, data = mtcars)
yuce(mtcars_lm, method = "A")
yuce(mtcars_lm, method = "B")
Run the code above in your browser using DataLab