cpcq.test <- function(covmats, nvec, B = cpc::FG(covmats = covmats, nvec = nvec)$B, q)
{
# covmats: array of covariance matrices to be tested for CPC vs. complete heterogeneity
# nvec: vector of sample sizes of the k groups
# B: modal matrix with the q common eigenvectors in the first q columns
# q: number of common eigenvectors (in B)
k <- dim(covmats)[3]
p <- dim(covmats)[1]
B1 <- B[, c(1:q)]
B2 <- B[, c((q + 1):p)]
covmats.cpcq <- array(NA, dim = c(p, p, k))
for(i in 1:k){
Q <- eigen(t(B2) %*% covmats[, , i] %*% B2)$vectors
Bi <- cbind(B1, B2 %*% Q)
Li <- diag(diag(t(Bi) %*% covmats[, , i] %*% Bi))
covmats.cpcq[, , i] <- Bi %*% Li %*% t(Bi)
}
chi2total <- 0
for(i in 1:k){
chi2total <- chi2total + (nvec[i] - 1) * log(det(covmats.cpcq[, , i]) / det(covmats[, , i]))
}
df <- k * (0.5 * p * (p - 1) + p) - (0.5 * p * (p - 1) + k * p + 0.5 * (k - 1) * (p - q) * (p - q - 1))
return(list(chi.square = chi2total, df = df, covmats.cpcq = covmats.cpcq))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.