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

Question

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)
ad.test(x,y)

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

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/… .
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 Finding or implementing a GoF test, whether in R or any other language, fits squarely within our interest in all things statistical.
@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 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.

momeara · Answer 1 · 2012-01-10 14:18:19Z

up vote 2 down vote

install.packages("adk")
library(adk)
adk.test(runif(50), rnorm(30))

answered Jan 10 '12 at 14:18

momeara
1507

1 Answer