Test of Homogeneity of Covariance Matrices given by Srivastava 2007
Srivastava2007(x, ...)
| 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. S. (2007). Testing the equality of two covariance matrices and independence of two sub-vectors with fewer observations than the dimension. InInternational Conference on Advances in InterdisciplinaryStistics and Combinatorics, University of North Carolina at Greensboro, NC, USA.
irisSpecies <- unique(iris$Species) iris_ls <- lapply(irisSpecies, function(x){as.matrix(iris[iris$Species == x, 1:4])} ) names(iris_ls) <- irisSpecies Srivastava2007(iris_ls)#> #> Srivastava 2007 Homogeneity of Covariance Matrices Test #> #> data: setosa, versicolor and virginica #> Chi-Squared = -19.472, df = 2, p-value = 1 #> alternative hypothesis: true difference in covariance matrices is not equal to 0 #>