Test of Structure of a Covariance Matrix given by Ahmad and Rosen 2015

Ahmad2015(x, Sigma = "identity", ...)

## Arguments

x data Population covariance matrix other options passed to covTest method

## Value

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

 statistic the value of equality 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 equality of covariance test was performed

## Details

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

## References

Ahmad, M. R. and Rosen, D. von. (2015). Tests for High-Dimensional Covariance Matrices Using the Theory of U-statistics. Journal of Statistical Computation and Simulation, 85(13), 2619-2631. 10.1080/00949655.2014.948441

## Examples

Ahmad2015(as.matrix(iris[1:50, 1:3]))#>
#> 	Ahmad and Rosen 2015 Test of Covariance Matrix Structure
#>
#> data:
#> Normal = 24294, Mean = 0.0000, Variance = 7.5472, p-value < 2.2e-16
#> alternative hypothesis: true difference between the Sample Covariance Matrix and the Null Covariance Matrix Structure is not equal to 0
#> sample estimates:
#>              Sepal.Length Sepal.Width Petal.Length
#> Sepal.Length   0.12424898  0.09921633   0.01635510
#> Sepal.Width    0.09921633  0.14368980   0.01169796
#> Petal.Length   0.01635510  0.01169796   0.03015918
#>