Nothing
predict.liu <-
function(object, newdata, na.action = na.pass, terms = NULL, ...) {
#credit predict.lm
# tt <- terms(object)
tt <- attr(object$mf, "terms")
if (!inherits(object, "liu"))
warning("calling predict.liu(<fake-liu-object>) ...")
if (missing(newdata) || is.null(newdata)) {
mm <- X <- model.frame(object)
mmDone <- TRUE
#offset <- object$offset
}
else {
Terms <- delete.response(tt)
m <- model.frame(Terms, newdata, na.action = na.action)
if (!is.null(cl <- attr(Terms, "dataClasses")))
.checkMFClasses(cl, m)
mm <- X <- model.matrix(Terms, m)
# offset <- rep(0, nrow(X))
if (!is.null(off.num <- attr(tt, "offset")))
for (i in off.num)
offset <-
offset + eval(attr(tt,"variables")[[i + 1]], newdata)
# if (!is.null(object$call$offset))
# offset <- offset + eval(object$call$offset, newdata)
# mmDone <- FALSE
}
intercept <- attr(tt, "intercept")
tlabel <- attr(tt, "term.labels")
if (intercept) {
mm <- cbind(1, X[,tlabel])
}else{
mm <- X[,tlabel]
}
beta <- coef(object)
if (length(object$d) > 1 & nrow(X) > 1)
res <- apply(beta, 1, function(x) {
drop(as.matrix(mm) %*% x)
})
else if (length(object$d) > 1 & nrow(X) == 1) {
res <- lapply(1:length(object$d), function(i, mm, beta) {
c(1,mm[,-1]) %*% beta[i,]
}, mm = mm, beta = beta)
res <- do.call(cbind, res)
colnames(res) <- paste("d=|", object$d, sep = "")
}
else if (length(object$d) == 1 & nrow(X) > 1) {
res <- drop(as.matrix(mm) %*% beta)
}
else
res <- drop(t(as.matrix(c(1,mm[,-1]))) %*% beta)
res
}
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