Test of Structure of a Covariance Matrix given by Fisher 2012
Fisher2012(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.
Fisher, T. J. (2012). On Testing for an Identity Covariance Matrix when the Dimensionality Equals or Exceeds the Sample Size. Journal of Statistical Planning and Infernece, 142(1), 312-326. 10.1016/j.jspi.2011.07.019
Fisher2012(as.matrix(iris[1:50, 1:4]))#> #> Fisher 2012 Test of Covariance Matrix Structure #> #> data: #> Standard Normal = 5.6235, Mean = 0, Variance = 1, p-value = 9.354e-09 #> 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 Petal.Width #> Sepal.Length 0.12424898 0.099216327 0.016355102 0.010330612 #> Sepal.Width 0.09921633 0.143689796 0.011697959 0.009297959 #> Petal.Length 0.01635510 0.011697959 0.030159184 0.006069388 #> Petal.Width 0.01033061 0.009297959 0.006069388 0.011106122 #>