Test of Homogeneity of Covariance Matrices given by Srivastava et al. 2014

Srivastava2014(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.


Srivastava, M., Yanagihara, H., and Kubokawa T. (2014). Tests for covariance matrices in high dimension with less sample size. Journal of Multivariate Analysis, 130:289-309. 10.1016/j.jmva.2014.06.003


irisSpecies <- unique(iris$Species) iris_ls <- lapply(irisSpecies, function(x){as.matrix(iris[iris$Species == x, 1:4])} ) names(iris_ls) <- irisSpecies Srivastava2014(iris_ls)
#> #> Srivastava et al. 2014 Homogeneity of Covariance Matrices Test #> #> data: setosa, versicolor and virginica #> Chi-Squared = 1007.8, df = 1, p-value < 2.2e-16 #> alternative hypothesis: true difference in covariance matrices is not equal to 0 #>