Kullback {asbio} | R Documentation |
Provides Kullback's (1959) test for multivariate homoscedasticity.
Kullback(Y, X)
Y |
An n x p matrix of quantitative variables |
X |
An n x 1 vector of categorical assignments (e.g. factor levels) |
Multivariate general linear models assume equal covariance matrices for all factor levels or factor level combinations. Legendre and Legendre (1998) recommend this test for verifying homoscedsticiy. P-values evaluate a null hypothesis of equal population covariance matrices.
Returns a dataframe with the test statistic (which follows a chi-square distribution if H_0 is true), the chi-square degrees of freedom, and the calculated p-value.
Ken Aho
Kullback, S. (1959) Information theory and statistics. John Wiley and Sons.
Legendre, P, and Legendre, L. (1998) Numerical ecology, 2nd English edition. Elsevier, Amsterdam, The Netherlands.
Y1<-rnorm(100,10,2) Y2<-rnorm(100,15,2) Y<-cbind(Y1,Y2) X<-factor(c(rep(1,50),rep(2,50))) Kullback(Y,X)