Test of Structure of a Covariance Matrix given by Ledoit and Wolf 2002
LedoitWolf2002(x, Sigma = "identity", ...)
| x | data |
|---|---|
| Sigma | Population covariance matrix |
| ... | other options passed to covTest method |
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 |
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
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 #>