From: Kurt Hornik <Kurt.Hornik_at_wu-wien.ac.at>

Date: Mon 03 Apr 2006 - 11:30:07 GMT

R-devel@r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-devel Received on Mon Apr 03 21:58:47 2006

Date: Mon 03 Apr 2006 - 11:30:07 GMT

>>>>> gael millot writes:

> Full_Name: Gael Millot

*> Version: 2.2.0.
**> OS: XP
**> Submission from: (NULL) (195.220.102.20)
*

> Hello.

> I sent an Email in r-help without answer for the moment.

> I am wondering if it could have a mistake

*> in the code of the ansari.test function. For me, it seems that the function
**> do not recover the p value at the correct side of the normal law N(0, 1) when it
**> use
**> the normal approximation (presence of ties) in a one tailed test.
*

> Here is what is written in ansari.test :

*> p <- pnorm(normalize(STATISTIC, r, TIES))
**> PVAL <- switch(alternative,
**> two.sided = 2 * min(p, 1 - p),
**> less = 1 - p,
**> greater = p)
*

> pnorm() is written without "lowertail = FALSE". So it should be :

*> less = p
**> greater = 1-p
*

> Am I wrong ???

> Thanks very much for your help.

I think the code does what the docs say:

Suppose that 'x' and 'y' are independent samples from distributions with densities f((t-m)/s)/s and f(t-m), respectively, where m is an unknown nuisance parameter and s, the ratio of scales, is the parameter of interest. The Ansari-Bradley test is used for testing the null that s equals 1, the two-sided alternative being that s != 1 (the distributions differ only in variance), and the one-sided alternatives being s > 1 (the distribution underlying 'x' has a larger variance, '"greater"') or s < 1 ('"less"').

-k

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Mon Apr 03 21:58:47 2006

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