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# nonlinear ranking selection
selnlrs = function(fitvals, ns, selns, ...){
n = length(fitvals)
if(missing(ns)) ns=n
if(missing(selns)) selns=0.5
fitranks = (n+1)-rank(fitvals, ties.method="min")
fstar= selns*(1-selns)^(fitranks-1)
p = pmin(pmax(0, fstar/sum(fstar)), 1)
matpool = sample(1:n, size=ns, prob=p, replace=TRUE)
return(matpool)
}
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