Test of Structure of a Covariance Matrix given by Ledoit and Wolf 2002

LedoitWolf2002(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.

Ledoit, O., and Wolf, M. (2002). Some Hypothesis Tests for the Covariance Matrix When the Dimension Is Large Compared to the Sample Size. The Annals of Statistics, 30(4), 1081-1102. 10.1214/aos/1031689018

## Examples

LedoitWolf2002(as.matrix(iris[1:50, 1:3]))#>
#> 	Ledoit and Wolf 2002 Test of Covariance Matrix Structure
#>
#> data:
#> Chi Squared = 65.988, df = 6, p-value = 2.71e-12
#> 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
#>