Nothing
`kmNoNugget.init` <-
function(model, fn, fnscale) {
parinit <- model@parinit
ninit <- model@control$pop.size
param.n <- model@covariance@param.n
if (length(parinit) > 0) {
matrixinit <- matrix(parinit, nrow = param.n, ncol = ninit)
} else {
lower <- model@lower
upper <- model@upper
if (existsMethod("paramSample", signature = class(model@covariance))) {
matrixinit <- paramSample(model@covariance, n=ninit, lower=lower, upper=upper, y=model@y)
} else {
# sample ninit design points, generated from uniform [lower, upper]
matrixinit <- matrix(runif(ninit*param.n), nrow = param.n, ncol = ninit)
matrixinit <- lower + matrixinit*(upper - lower)
}
}
# take the best point(s)
fninit <- apply(matrixinit, 2, fn, model)
selection <- sort(fninit, decreasing = (fnscale < 0), index.return = TRUE)$ix
selection <- selection[1:model@control$multistart]
parinit <- matrixinit[, selection, drop = FALSE]
# for one point : parinit <- matrixinit[, which.max(fninit), drop = FALSE]
covinit <- list()
for (i in 1:model@control$multistart){
covinit[[i]] <- vect2covparam(model@covariance, parinit[,i])
}
return(list(par = parinit,
value = fninit[selection],
cov = covinit,
lower = model@lower,
upper = model@upper))
}
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