R Box'M test for homocedasticity

Question

I'm trying to replicate a linear discriminant analysis output from SPSS in R, and I'm having difficulties to find a way to perform an m-box test.

The only thing I found was some code posted in a forum, to manually implement the process, but I was wondering if there is nothing for this purpose already incorporated in the language itself.

Answer 1

There is code that can be found with a simple rseek search. It's not typically done because it's very high sensitivity leads to significant p-values that may not mean much.

EDIT: That old link doesn't work anymore but it turns out that the test is implemented in the biotools package with the function boxM. It was still a relatively easy search. And it's still true that you probably shouldn't bother using it like all such tests. You should probably just carefully examine your covariance matrix and your assumptions.

Answer 2

In package biotools you can find the function boxM(data, grouping). It performs the Box's M-test for homogeneity of covariance matrices obtained from multivariate normal data according to one classification factor. The test is based on the chi-square approximation.