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#' @importFrom stats dnorm pnorm predict
#' @keywords internal
calcAcq <- function(par, scoreGP, timeGP, acq, y_max, kappa, eps) {
# Excellent paper showing the derivation of each utility funciton.
# https://www.cse.wustl.edu/~garnett/cse515t/spring_2015/files/lecture_notes/12.pdf
# DiceKriging requires columns
p <- matrix(par,ncol=length(par),dimnames = list(NULL,names(par)))
GP_Pred <- predict(scoreGP,p,type="SK")
if (acq == "ucb") {
return((GP_Pred$mean + kappa * (GP_Pred$sd)))
} else if (acq == "ei") {
z <- (GP_Pred$mean - y_max - eps) / (GP_Pred$sd)
return(((GP_Pred$mean - y_max - eps) * pnorm(z) + (GP_Pred$sd) * dnorm(z)))
} else if (acq == "eips") {
GPe_Pred <- predict(timeGP,p,type="SK")
z <- (GP_Pred$mean - y_max - eps) / (GP_Pred$sd)
return(((GP_Pred$mean - y_max - eps) * pnorm(z) + (GP_Pred$sd) * dnorm(z))/GPe_Pred$mean)
} else if (acq == "poi") {
z <- (GP_Pred$mean - y_max - eps) / (GP_Pred$sd)
return((pnorm(z)))
}
}
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