Test of Equality of Covariances given by Srivastava and Yanagihara 2010

SrivastavaYanagihara2010(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. and Yanagihara, H. (2010). Testing the equality of several covariance matrices with fewer observation that the dimension. Journal of Multivariate Analysis, 101(6):1319-1329. 10.1016/j.jmva.2009.12.010


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 #>