Koen Vermeer wrote:
> 
> Hi,
> 
> I want to test whether a set is drawn from a normal distribution. With a
> Kolmogorov-Smirnov test, I can do this for known mean and variance. The
> Lilliefors test is essentially the same, but for unknown mean and variance
> (thus estimated from the data).
> Now, in my case, I have a known mean (zero) and unknown variance, meaning
> that my situation is somewhere in between Kolmogorov-Smirnov and
> Lilliefors. Is there a separate test for this?

Not that I know of, but there's a lot of things I don't know. :-)

> I haven't checked the
> Lilliefors paper yet, so maybe I am able to partly follow the paper and
> come up with a similar result for known mean and unknown variance, but if
> someone else has already done it, I'd rather use those results.
> 
> Any comments on this?
> 
> Regards,
> Koen Vermeer

I'd run both using your known mean and an estimate of the variance
and see what the results are.  If your set passes both with flying
colors I wouldn't worry about it.  If both are marginal or it
fails one then maybe you need to examine the situation further.
Here's a reference about an order statistic I developed which can
be used to test data against assumed distributions: Martin, R. L.,
"A Statistic Useful for Characterizing Probability Distributions,
with Application to Rain Rate Data", J. Appl. Meteor., 28, 354 (1989).
I don't know if it would be useful in your case or not.  I could
send you a reprint if you don't have access to _Journal of Applied
Meteorology_.

Regards,
Russell
.
.
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