Nothing
`predict.prcurve` <- function(object, newdata, ...) {
if(missing(newdata))
return(fitted(object))
## check the variable names in newdata match with original data
## essentially, this will only work if the names match, hence
## join() likely useful for the user
nNew <- colnames(newdata)
nData <- colnames(object$data)
if (!isTRUE(all.equal(nNew, nData))) {
if (isTRUE(all.equal(sort(nNew), sort(nData)))) {
newdata <- newdata[, nData]
} else {
stop("Variables in 'newdata' don't match with training datat.")
}
}
## otherwise project points on to the curve
p <- project_to_curve(data.matrix(newdata), s = object$s,
stretch = object$stretch)
out <- p$s
attr(out, "tag") <- p$ord
out
}
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