Nothing
pred.genv <- function(m, Xnew, Znew){
if (is.null(m$ratio))
stop("The asymptotic distribution part of genv is missing. Rerun genv with asy = T")
r <- ncol(m$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(Znew, Ind))
if (is.null(m$Gamma)) {
u <- 0
}
else {
u <- ncol(m$Gamma)
}
if (u == 0) {
value <- m$mu
covMatrix.estm <- m$Sigma/n
covMatrix.pred <- (1 + 1/n) * m$Sigma
}
else {
Xnew <- as.matrix(Xnew)
if (nrow(Xnew) == 1)
Xnew <- t(Xnew)
mu <- m$mu
beta <- m$beta
value <- mu[ ,t] + beta[[t]] %*% Xnew
temp <- kronecker(Xnew, diag(r))
covMatrix.estm <- m$Sigma[[t]]/ng[[t]] + crossprod(temp,
m$covMatrix[[t]]) %*% temp/ng[[t]]
covMatrix.pred <- (1 + 1/ng[[t]]) * m$Sigma[[t]] + crossprod(temp,
m$covMatrix[[t]]) %*% temp/ng[[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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