Perhaps the problem stands on the rbs function which generates random samples from the Birnbaum-Saunders distribution: > library(bs) > set.seed(1) > x<-rbs(n=1000,alpha=0.5,beta=1.0) > # sample mean > mean(x) [1] 1.117749 > # expected value > beta*(1+alpha^2/2) [1] 2.125 > # so different!
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