Nothing
predict.svocc <-
function(object, newdata = NULL, type = c("link", "response"),
model = c("sta", "det"), se.fit = FALSE, ...){
type <- match.arg(type)
model <- match.arg(model)
if (se.fit) {
boot <- attr(object, "bootstrap")
if (is.null(boot))
stop("cannot provide prediction Std Error without Bootstrap")
Bp <- ncol(boot)
nps <- sapply(object$coefficients, length)
id <- switch(model,
sta = 1:nps[1],
det = (nps[1]+1):sum(nps[1:2]))
}
if (is.null(newdata)) {
rval <- switch(model,
sta = object$occurrence.probabilities,
det = object$detection.probabilities)
if (type == "link")
rval <- binomial(object$link[[model]])$linkfun(rval)
if (se.fit)
X <- model.matrix(object, model)
} else {
ff <- object$formula[[model]]
if (model == "sta")
ff[[2]] <- NULL
rhs <- model.frame(ff, newdata)
X <- model.matrix(attr(rhs, "terms"), rhs)
rval <- drop(X %*% coef(object, model))
if (type == "response")
rval <- binomial(object$link[[model]])$linkinv(rval)
}
if (se.fit) {
se <- sapply(1:Bp, function(i) drop(X %*% boot[id,i]))
if (type == "response")
se <- binomial(object$link[[model]])$linkinv(se)
se <- apply(se, 1, sd)
rval <- list(fit = rval, se.fit = se)
}
rval
}
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