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.

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
#>