>>>>> 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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