Description Usage Arguments Value References See Also Examples
Tests the difference between two successive relative eigenvalues
1 | eigen.test(n, relValues)
|
n |
the sample size(s), given as a number or a vector of length 2 |
relValues |
a vector of relative eigenvalues |
The P-values for the test of difference between successive eigenvalues
Mardia KV, Kent JT, Bibby JM (1979) Multivariate analysis. Academic Press, London.
relative.eigen
for the computation of relative eigenvalues,
pchisq
for Chi-squared distribution
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # Data matrix of 2D landmark coordinates
data("Tropheus.IK.coord")
coords <- which(names(Tropheus.IK.coord) == "X1"):which(names(Tropheus.IK.coord) == "Y19")
proc.coord <- as.matrix(Tropheus.IK.coord[coords])
# Data reduction
phen.pca <- prcomp(proc.coord, rank. = 5, tol = sqrt(.Machine$double.eps))
pc.scores <- phen.pca$x
# Covariance matrix of each population
S.phen.pop <- cov.group(pc.scores, groups = Tropheus.IK.coord$POP.ID)
# Relative PCA = relative eigenanalysis between 2 covariance matrices
# (population IKA1 relative to IKS5)
relEigen.a1s5 <- relative.eigen(S.phen.pop[, , "IKA1"], S.phen.pop[, , "IKS5"])
# Test of the difference between 2 successives eigenvalues
# of the covariance matrix of IKA1 relative to IKS5
n_ika1 <- length(which(Tropheus.IK.coord$POP.ID == "IKA1")) # sample size for IKA1
n_iks5 <- length(which(Tropheus.IK.coord$POP.ID == "IKS5")) # sample size for IKS5
eigen.test(n = c(n_ika1, n_iks5), relValues = relEigen.a1s5$relValues)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.