In article <[EMAIL PROTECTED]>,
Andrew Morse  <[EMAIL PROTECTED]> wrote:

>Three questions, in increasing order of generality...

>    1.  Does a general method exist for calculating the expected 
>standard deviation of N samples taken from an arbitrary, known 
>probability distribution?

Do you mean samples of size N?  And do you mean the sample
standard deviation, or what?  However, the answer is very
likely to be no; square roots mess things up.

>    2.  Does a general method exist for calculating the expected 
>distribution of standard deviations of repeated trials of N samples 
>taken from an arbitrary, known probability distribution?

This can only be done in closed form for a few
distributions.  This even applies to the simpler problem of
the second moment about 0.  Using complex variable methods,
it may well be possible to do it numerically in a reasonable
amount of time.

The general method for this, if it can be done, is to compute
the characteristic function of the moment, raise it to the N-th
power, and invert.

>    3.  Does a general method exist for calculating the expected 
>distribution of any of the moments of repeated trials of N samples taken 
>from an arbitrary, known probability distribution?

The same remarks as above hold.

If the 2k-th moment exists, the Central Limit Theorem gives
the asymptotic normal distribution of the k-th moment about 0.
Similar results hold for ths standard deviation of th fourth
moment exists.  These asymptotic results are very old.
-- 
This address is for information only.  I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Department of Statistics, Purdue University
[EMAIL PROTECTED]         Phone: (765)494-6054   FAX: (765)494-0558
.
.
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