Test of Equality of Covariances given by Srivastava and Yanagihara 2010

SrivastavaYanagihara2010(x, ...)

## Arguments

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

## Value

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

## Details

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

## References

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

## Examples

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
#>