On Fri, 06 Dec 2002 16:04:50 +0100, "Koen Vermeer"
<[EMAIL PROTECTED]> wrote:

> On Fri, 06 Dec 2002 09:24:16 +0000, Herman Rubin wrote:
> 
> >>I am not very familiar with the Anderson-Darling test. I only know it is
> >>an alternative to KS and it is not distribution free. The last thing was
> >>the mean reason I wasn't considering it for the moment. Maybe I'll have a
> >>look at it in th near future.
> > The Anderson-Darling test is as distribution free as the 
> > Kolmogorov-Smirnov.
> 
> Hmm, I thought I read somewhere that the KS test statistic is independent of the
> distribution that is tested against. Maybe I'm mistaken...

The URL below has a description that confirms the thought.  
Their modification of the K-S  makes use of particular distributions
to make a more powerful test.

http://www.itl.nist.gov/div898/handbook/eda/section3/eda35e.htm

Below is a comprehensive posting to  sci.stat.math  by  "Ken K" 
on April 25, 2001.  
It cites the address above, and it quotes D'Agostino & Stephens.
This is the main text of his post, which I found by googling 
in the sci.stat.*  groups for Anderson-Darling.

============= start of post
Try the NIST/Sematech On-line Engineering Statistics Handbook, and
specifically the EDA section. Here is a link to the main handbook,
which is pretty nice:

http://www.itl.nist.gov/div898/handbook/index.htm

The EDA section is listed under the Explore link.

If you go to
http://www.itl.nist.gov/div898/handbook/eda/section3/eda35.htm
you'll find near the bottom of the page links to explanations covering
the Anderson-Darling, Chi-Square, and Kolmogorov-Smirnov tests.

And a word of warning from D'Agostino & Stephens' "Goodness-of-Fit
Techniques" book (published by Marcel-Dekker, Inc.), page 406:

"6. For testing for normality, the Kolmogorov-Smirnov test is only a
historical curiosity. It should never be used. It has poor power in
comparison to the above procedures**.

7. For testing normality, when a complete sample is available the
chi-square test should not be used. It does not have good power when
compared to the above tests**."


**Shapiro-Wilks W test, D'Agostino-Pearson K^2 test, Bowman-Shenton
version K(2,S), and Anderson-Darling edf test A^2 - also the R test
and D'Agostino's  D test.
=========== end of Ken's comments.

-- 
Rich Ulrich, [EMAIL PROTECTED]

http://www.pitt.edu/~wpilib/index.html
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