# [Rd] PR#896

**Torsten Hothorn
**
Torsten.Hothorn@rzmail.uni-erlangen.de

*Wed, 18 Apr 2001 11:44:11 +0200 (MEST)*

On 16 Apr 2001, Peter Dalgaard BSA wrote:
>* Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de> writes:
*>*
*>* > > c(3.770684,4.654342,3.496403,1.772743,1.624953,2.645835,3.0994
*>* > > 77,1.706758,3.507709,1.982924)
*>* > > y<-c(-0.8161288,0.1632923,0.6421997,1.9270846,-
*>* > > 0.4668112,0.3587806,0.3312529,-0.5393900,
*>* > > 0.1057892,1.7963575)
*>* >
*>* > `wdiff' is used for the computation of asymptotic confidence intervals for
*>* > samples with m,n > 50. I simulated the type I error rate and it works for
*>* > such large sample sizes. So maybe the problems are due to n.x = n.y = 10 ?
*>* >
*>* > Torsten
*>*
*>* I think the real problem is here:
*>*
*>* > > ol<-optimize(wdiff,c(mumin,mumax),zq=qnorm(0.05))$minimum
*>* > > om<-optimize(wdiff,c(mumin,mumax),zq=qnorm(0.5))$minimum
*>* > > ou<-optimize(wdiff,c(mumin,mumax),zq=qnorm(0.95))$minimum
*>* > >
*>* > > abline(v=ol)
*>* > > abline(v=om,lty=4)
*>* > > abline(v=ou,lty=7)
*>*
*>* Optimize() is a gradient algorithm and wdiff is not smooth, so the
*>* algorithm terminates at a stationary non-optimal point. Using optim()
*>* with the default Nelder-Mead instead seemed to work better, although
*>* not perfectly. (I played with this before going on Easter holiday, and
*>* I'm not going to reconstruct exactly what I did then just now....)
*
Yes. We replaced `optimize' by `uniroot' in `wilcox.test' and use `optim'
in `ansari.test' now.
Torsten
>*
*>* --
*>* O__ ---- Peter Dalgaard Blegdamsvej 3
*>* c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
*>* (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
*>* ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk) FAX: (+45) 35327907
*>*
*
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