However, if you know the point(s) of truncation then you should be able to
work your way back. Look for the mean and variance of a truncated normal, it
will involve mu, sigma and c (point of truncation). You will need to solve
for mu and sigma from two equation. For example look at the wikipedia page
on normal distribution, it has the mean of a truncated normal distribution.
Many standard statistics books should have the rest of the information.

On 9/12/06, Berton Gunter <gunter.berton@gene.com> wrote:
>
> >
> > But my question is a bit different. What I know is the mean
> > and sd after truncation. If I assume the distribution is
> > normal, how I am gonna develope the original distribution
> > using this two parameters?
>
> You can't, as they are plainly not sufficient (you need to know the amount
> of truncation also). If you have only the mean and sd and neither the
> actual
> data nor the truncation point you're through.
>
> -- Bert Gunter
> Genentech
>
>
> Could anybody give me some advice?
> > Thanks in advance!
> >
> > Jen
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch 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.
> >
>
> ______________________________________________
> R-help@stat.math.ethz.ch 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.
>



-- 
Ritwik Sinha
Graduate Student
Epidemiology and Biostatistics
Case Western Reserve University

http://darwin.cwru.edu/~rsinha

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