Test of Structure of a Covariance Matrix given by Ahmad and Rosen 2015

Ahmad2015(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.

Ahmad, M. R. and Rosen, D. von. (2015). Tests for High-Dimensional Covariance Matrices Using the Theory of U-statistics. Journal of Statistical Computation and Simulation, 85(13), 2619-2631. 10.1080/00949655.2014.948441

Ahmad2015(as.matrix(iris[1:50, 1:3]))#> #> Ahmad and Rosen 2015 Test of Covariance Matrix Structure #> #> data: #> Normal = 24294, Mean = 0.0000, Variance = 7.5472, p-value < 2.2e-16 #> 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 #>