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.

## References

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
#>