Perhaps there's a problem with the function rbs, that generates a random sample from the Birnbaum-Saunders distribution. The rgbs function (package gbs) does it better. Look at these code and results: > library(bs) > set.seed(1) > alpha<-0.17 > beta<-130 > x<-rbs(n=1000,alpha,beta) > # sample mean > mean(x) [1] 150.8288 > # expected value > beta*(1+alpha^2/2) [1] 131.8785 > est1bs(x) $beta.start [1] 149.9556
$alpha [1] 0.1079173 $beta [1] 149.9558 $converge [1] "TRUE" $iteration [1] 2 > #not fine > library(gbs) > # > set.seed(1) > x<-rgbs(n=1000,alpha,beta) > # sample mean > mean(x) [1] 131.7481 > # expected value > beta*(1+alpha^2/2) [1] 131.8785 > est1bs(x) $beta.start [1] 129.7422 $alpha [1] 0.1758475 $beta [1] 129.7421 $converge [1] "TRUE" $iteration [1] 2 > #fine -- View this message in context: http://r.789695.n4.nabble.com/Status-of-the-bs-Package-tp827806p3033734.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
