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## CGF (and its derivatives) of the aggregate loss process at time 1.0
K <- function(model) {
function(x, difforder = 0L) {
mx <- sdprisk::mgfhypoexp(x = x,
rate = model$rates,
difforder = difforder)
difforder <- match(difforder, 0L:2L, 4L)
is.na(x) <- vapply(x >= min(model$rates), isTRUE, logical(1L))
drop(crossprod(c(model$freq, model$premium, model$variance),
switch(difforder,
rbind(mx - 1.0, -x, 0.5 * x^2.0),
rbind(mx, -1.0, x),
rbind(mx, 0.0, 1.0))))
}
}
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