Test of Structure of a Covariance Matrix given by Fisher 2012

Fisher2012(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

Fisher, T. J. (2012). On Testing for an Identity Covariance Matrix when the Dimensionality Equals or Exceeds the Sample Size. Journal of Statistical Planning and Infernece, 142(1), 312-326. 10.1016/j.jspi.2011.07.019

## Examples

Fisher2012(as.matrix(iris[1:50, 1:4]))#>
#> 	Fisher 2012 Test of Covariance Matrix Structure
#>
#> data:
#> Standard Normal = 5.6235, Mean = 0, Variance = 1, p-value = 9.354e-09
#> 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 Petal.Width
#> Sepal.Length   0.12424898 0.099216327  0.016355102 0.010330612
#> Sepal.Width    0.09921633 0.143689796  0.011697959 0.009297959
#> Petal.Length   0.01635510 0.011697959  0.030159184 0.006069388
#> Petal.Width    0.01033061 0.009297959  0.006069388 0.011106122
#>