`homogeneityCovariances.Rd`

Performs 2 and k sample homogeneity of covariance matrices test using test, 'covTest.'

homogeneityCovariances(x, ..., covTest = BoxesM)

x | data as a data frame, list of matrices, grouped data frame, or resample object |
---|---|

... | other options passed to covTest method |

covTest | homogeneity of covariance matrices test method |

A list with class "htest" containing the following components:

`statistic` | the value of homogeneity 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 homogeneity of covariance test was performed |

`data.name` | a character string giving the names of the data |

The `homogeneityCovariances`

function is a wrapper function that formats the data
for the specific `covTest`

functions.

Other Testing for Homogeneity of Covariance Matrices: `Ahmad2017`

homogeneityCovariances(iris, group = Species)#> #> Boxes' M Homogeneity of Covariance Matrices Test #> #> data: setosa, versicolor and virginica #> Chi-Squared = 146.66, df = 2550, p-value = 1 #> alternative hypothesis: true difference in covariance matrices is not equal to 0 #>