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 #>