unexpected behaviour of rnorm()
That's the maximum of 5000 normals, right? That's pushing the accuracy of some internal calculations too hard. If you want to do this, you should use RNGkind(, "Inversion") That's not the default for back-compatibility reasons.
On Wed, 27 Nov 2002, Robin Hankin wrote:
Hello everyone.
If I do
f <- function(n){max(rnorm(n))}
plot(sapply(rep(5000,4000),f)) #[this takes my PC about 30 seconds]
then I get something quite unexpected: gaps in the distribution. For
me, the most noticable one is at about 3.6.
Do others get this? Is it an optical illusion? It can't be right,
can it? Or maybe I just don't understand the good ol' Gaussian very
well.
anyone got an explanation?
[linux redhat 7.1; R-1.6.1]
--
Robin Hankin, Lecturer,
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