Test of Homogeneity of Covariance Matrices given by Chaipitak and Chongcharoen 2013

Chaipitak2013(x, ...)



data as a data frame, list of matrices, grouped data frame, or resample object


other options passed to covTest method


A list with class "htest" containing the following components:

statistic the value of homogeneity of covariance test statistic
parameter the degrees of freedom for the chi-squared statistic
p.value the p=value for the test
estimate the estimated covariances if less than 5 dimensions
null.value the specified hypothesized value of the covariance difference
alternative a character string describing the alternative hyposthesis
method a character string indicating what type of homogeneity of covariance test was performed


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


Chaipitak, S. and Chongcharoen, S. (2013). A test for testing the equality of two covariance matrices for high-dimensional data. Journal of Applied Sciences, 13(2):270-277. 10.3923/jas.2013.270.277


irisSpecies <- unique(iris$Species) iris_ls <- lapply(irisSpecies, function(x){as.matrix(iris[iris$Species == x, 1:4])} ) names(iris_ls) <- irisSpecies Chaipitak2013(iris_ls)
#> #> Chaipitak and Chongchareon 2013 Homogeneity of Covariance Matrices #> Test #> #> data: setosa, versicolor and virginica #> Chi-Squared = 5.901, df = 2, p-value = 0.05231 #> alternative hypothesis: true difference in covariance matrices is not equal to 0 #>