Nothing
robMD2 <- function(object)
{
m <- model.frame(object)
if(is.null(m))
return(rep(as.numeric(NA), length(fitted(object))))
m.terms <- terms(m)
X <- model.matrix(m.terms, m)
dc <- attr(m.terms, "dataClasses")
tl <- attr(m.terms, "term.labels")
numeric.vars <- intersect(tl, names(dc)[dc == "numeric"])
if(length(numeric.vars)) {
X2 <- as.matrix(m[numeric.vars])
mcd <- covMcd(X2)
w <- mcd$mcd.wt
sum.w <- sum(w)
mu <- apply(X2, 2, weighted.mean, w = w)
X2.tilde <- sweep(X2, 2, mu)
X2.tilde <- sqrt(prod(mcd$cnp) * (nrow(X2.tilde) - 1)/(sum.w - 1)) * w * X2.tilde
m[numeric.vars] <- sweep(X2.tilde, 2, mu, FUN = "+")
}
D <- model.matrix(m.terms, m)
if(attr(m.terms, "intercept")) {
X <- X[, -1, drop = FALSE]
D <- D[, -1, drop = FALSE]
}
stats::mahalanobis(X, colMeans(D), var(D))
}
designMD.lmRob <- function(object, ...)
robMD2(object)
## Methods for other packages ##
designMD.lmrob <- function(object, ...)
robMD2(object)
designMD.glmrob <- function(object, ...)
robMD2(object)
designMD.rlm <- function(object, ...)
robMD2(object)
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