https://github.com/cran/robCompositions
Tip revision: 37555063454f14ae40f041b3a8f0eb2d3dc3be4c authored by Matthias Templ on 10 January 2011, 00:00:00 UTC
version 1.4.4
version 1.4.4
Tip revision: 3755506
pcaCoDa.R
pcaCoDa <- function(x, method="robust"){
# Closure problem with ilr transformation
ilrV <- function(x){
# ilr transformation
x.ilr=matrix(NA,nrow=nrow(x),ncol=ncol(x)-1)
for (i in 1:ncol(x.ilr)){
x.ilr[,i]=sqrt((i)/(i+1))*log(((apply(as.matrix(x[,1:i]), 1, prod))^(1/i))/(x[,i+1]))
}
return(x.ilr)
}
xilr <- ilrV(x)
if( method == "robust"){
cv <- covMcd(xilr, cor=FALSE)
pcaIlr <- suppressWarnings(princomp(xilr, covmat=cv, cor=TRUE))
eigenvalues <- eigen(cv$cov)$values
} else {
pcaIlr <- princomp(xilr, cor=TRUE)
eigenvalues <- eigen(cov(xilr))$values
}
# construct orthonormal basis
V <- matrix(0, nrow=ncol(x), ncol=ncol(x)-1)
for( i in 1:ncol(V) ){
V[1:i,i] <- 1/i
V[i+1,i] <- (-1)
V[,i] <- V[,i]*sqrt(i/(i+1))
}
# robust ilr result - back-transformed to clr-space
loadings <- V %*% pcaIlr$loadings
dimnames(loadings)[[1]] <- names(x)
pcaClr <- pcaIlr
pcaClr$scores <- pcaIlr$scores %*% t(V)
pcaClr$loadings <- loadings
res <- list(scores = pcaClr$scores,
loadings = loadings,
eigenvalues = eigenvalues,
method = method,
princompOutputClr = pcaClr
)
class(res) <- "pcaCoDa"
invisible(res)
}