# Is there an anderson-darling goodness of fit test for two datasets?

I know ad.test() can be used for testing normality.

Is it possible to get ad.test compare the distribution of two data?

x=readcsv("mydata.csv", header=T)
y=rgev(2000)


How can I do Anderson Darling statistic for goodness of fit of two data?

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The Wikipedia article on the A-D test mentions this under the heading "Non-parametric k-sample tests." Its reference, a 1987 JASA paper by Sholz and Stephens, is freely available at cithep.caltech.edu/~fcp/statistics/hypothesisTest/… . –  whuber Jun 23 '11 at 16:05
If the question is: how can I do it in R (as the tag suggests): good question (+1) (and the answer is probably: rig it yourself), albeit somewhat misplaced here (StackOverflow is a better place for this kind of question). –  Nick Sabbe Jun 23 '11 at 19:00
@Nick Finding or implementing a GoF test, whether in R or any other language, fits squarely within our interest in all things statistical. –  whuber Jun 23 '11 at 19:13
@whuber: I stand corrected: I just read the relevant part of the faq. Still, it's a thin line between love and hate. But I didn't vote to migrate :-) –  Nick Sabbe Jun 23 '11 at 19:27
@Nick I agree about the thin line. When a question focuses purely on the mechanics of programming, its appropriateness here becomes doubtful. You can find periodic discussions about this on meta. –  whuber Jun 23 '11 at 20:19
install.packages("adk")