Seems there is an exact non-parametric Bayes test for mean of non-negative
numbers as said on
http://www.toad.net/~jkaplan2/martMean.htm<http://www.toad.net/~jkaplan2/martMean.htm#From%20bins>

I will check if R may have such package.

On 12/22/06, Ben Bolker <bolker@zoo.ufl.edu> wrote:
>
> 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
>
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