Test of Homogeneity of Covariance Matrices given by Ishii and Aoshima 2016
Ishii2016(x, ...)
| x | data as a data frame, list of matrices, grouped data frame, or resample object |
|---|---|
| ... | other options passed to covTest 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 |
The homogeneityCovariances function is a wrapper function that formats the data
for the specific covTest functions.
Ishii, A., Yata, K., and Aoshima, M. (2016). Asymptotic properties of the first pricipal component and equality tests of covariance matrices in high-dimesion, low-sample-size context. Journal of Statistical Planning and Inference, 170:186-199. 10.1016/j.jspi.2015.10.007
irisSpecies <- unique(iris$Species) iris_ls <- lapply(irisSpecies, function(x){as.matrix(iris[iris$Species == x, 1:4])} ) names(iris_ls) <- irisSpecies Ishii2016(iris_ls)#> #> Ishii and Aoshima 2016 Homogeneity of Covariance Matrices Test #> #> data: setosa, versicolor and virginica #> F = 4.6285, df1 = 3, df2 = 1, p-value = 0.3263 #> alternative hypothesis: true difference in covariance matrices is not equal to 0 #>