Message-ID: <loom.20061223T021858-795@post.gmane.org>
Date: 2006-12-23T01:22:57Z
From: Ben Bolker
Subject: nonparametric significance test for one sample
HelponR <suncertain <at> gmail.com> writes:
>
> Hi, Greg:
>
> Just let you know that the beta regression package in R can only work for
> data on the open interval (0, 1)
>
> Do you know any good test of mean for beta distribution? How to verify
> if the data is beta distributed?
>
> For example, I may want to test the null :
>
> mean <= 0.0000000001
>
> I think your idea of testing zero for nonnegative numbers makes sense. But
> it seems to make a null hypothesis on a distribution, not simply mean.
>
> I could be bettered off if I can find a good nonparametric test which does
> not assume symmetry or a test for beta distribution if the beta
> distribution can be verified.
>
> Many thanks,
>
> S
Possibly contrary to what the documentation for the
beta regression package, the beta distribution has
finite density for 0 and 1 _if_ the shape parameters
are large enough/variance parameter is small enough
(but probably this is not your situation, if you
have lots of zeros).
fitdistr() in the MASS package will give
a maximum-likelihood fit of the beta distribution
to a univariate distribution, but if you want
to calculate profile confidence limits etc. you
might want to look into the mle() function in
the stats4 package ...
Ben Bolker