[R] gamma distribution

[Christoph Buser]

Hi 

Again to come back on the question why you don't get identical
p.values for the untransformed and the transformed data.

I ran your script below and I get always 2 identical test per
loop. In your text you are talking about the first 1000 values
for the untransformed and the next 1000 values for the
transformed. 

But did you consider that in each loop there is a test for the
untransformed and the transformed, so the tests are printed
alternating. 
This might be a reason why you did not get equal results.

Hope this helps,

Christoph

--------------------------------------------------------------
Christoph Buser <buser at stat.math.ethz.ch>
Seminar fuer Statistik, LEO C13
ETH (Federal Inst. Technology)	8092 Zurich	 SWITZERLAND
phone: x-41-44-632-4673		fax: 632-1228
http://stat.ethz.ch/~buser/
--------------------------------------------------------------


pantd at unlv.nevada.edu writes:
 > Hi R Users
 > 
 > 
 > This is a code I wrote and just want to confirm if the first 1000 values are raw
 > gamma (z) and the next 1000 values are transformed gamma (k) or not. As I get
 > 2000 rows once I import into excel, the p - values beyond 1000 dont look that
 > good, they are very high.
 > 
 > 
 > --
 > sink("a1.txt");
 > 
 > for (i in 1:1000)
 > {
 > x<-rgamma(10, 2.5, scale = 10)
 > y<-rgamma(10, 2.5, scale = 10)
 > z<-wilcox.test(x, y, var.equal = FALSE)
 > print(z)
 > x1<-log(x)
 > y1<-log(y)
 > k<-wilcox.test(x1, y1, var.equal = FALSE)
 > print(k)
 > }
 > 
 > ---
 > any suggestions are welcome
 > 
 > thanks
 > 
 > -devarshi
 > 
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