Test of Homogeneity of Covariance Matrices given by Schott 2007

Test of Homogeneity of Covariance Matrices given by Schott 2007

Schott2007(x, ...)

Arguments

x	data as a data frame, list of matrices, grouped data frame, or resample object
...	other options passed to covTest method

Value

Test statistic of the hypothesis test

Details

The homogeneityCovariances function is a wrapper function that formats the data for the specific covTest functions.

References

Schott, J. (2007). A test for the equality of covariance matrices when the dimension is large relative to the sample sizes. Computational Statistics & Data Analysis, 51(12):6535-6542. 10.1016/j.csda.2007.03.004

Examples

irisSpecies <- unique(iris$Species)

iris_ls <- lapply(irisSpecies,
    function(x){as.matrix(iris[iris$Species == x, 1:4])}
                 )

names(iris_ls) <- irisSpecies

Schott2007(iris_ls)
#> 
#> 	Schott 2007 Homogeneity of Covariance Matrices Test
#> 
#> data:  setosa, versicolor and virginica
#> Chi-Squared = 2.0536e+16, df = 1, p-value < 2.2e-16
#> alternative hypothesis: true difference in covariance matrices is not equal to 0
#>