Nothing
pred.henv <- function (m, Xnew) {
if(is.null(m$ratio)) stop("The asymptotic distribution part of henv is missing. Rerun henv with asy = T")
r <- ncol(m$Sigma[[1]])
n <- m$n
ng <- m$ng
Ind <- m$groupInd
if (is.numeric(Ind)) {
Ind <- sort(Ind, index.return = T)$x
}
t <- which(Ind == intersect(Xnew, Ind))
covMatrix.estm <- NULL
covMatrix.pred <- NULL
SE.estm <- NULL
SE.pred <- NULL
if (is.null(m$Gamma)) {
u <- 0
}
else {
u <- ncol(m$Gamma)
}
if (u == 0) {
value <- m$mu
Sigma <- m$covMatrix[1 : r, 1 : r]
covMatrix.estm <- Sigma / n
covMatrix.pred <- Sigma / n + m$Sigma[[t]]
SE.estm <- sqrt(diag(covMatrix.estm))
SE.pred <- sqrt(diag(covMatrix.pred))
} else {
value <- m$mug[ , t]
aa = t * r + 1
bb = (t + 1) * r
covMatrix.estm <- (m$covMatrix[1 : r, 1 : r] + m$covMatrix[aa : bb, aa : bb]
+ m$covMatrix[1 : r, aa : bb]
+ m$covMatrix[aa : bb, 1 : r] / ng[t])
covMatrix.pred <- (m$covMatrix[1 : r, 1 : r] + m$covMatrix[aa : bb, aa : bb]
+ m$covMatrix[1 : r, aa : bb]
+ m$covMatrix[aa : bb, 1 : r] / ng[t]
+ m$Sigma[[t]])
SE.estm <- sqrt(diag(covMatrix.estm))
SE.pred <- sqrt(diag(covMatrix.pred))
}
return(list(value = value,
covMatrix.estm = covMatrix.estm, SE.estm = SE.estm,
covMatrix.pred = covMatrix.pred, SE.pred = SE.pred))
}
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