[R] ks.test() with 2 samples vs. 1 sample an distr. function

[David L Carlson]

In the first example you are performing a one-sample test against a continuous cumulative distribution (in this case a normal distribution). In the second case you are performing a two-sample test. You drew your values for x non-randomly by specifying fixed intervals along a normal distribution, but ks.test() just sees that you have provided two samples, not one sample and values along a cumulative distribution.

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David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77843-4352


-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of tonja.krueger at web.de
Sent: Wednesday, November 15, 2017 3:47 AM
To: r-help at r-project.org
Subject: [R] ks.test() with 2 samples vs. 1 sample an distr. function

Dear all,
I have a question concerning the ks.test() function. I tryed to calculate the example given on the German wikipedia page.
xi <- c(9.41,9.92,11.55,11.6,11.73,12,12.06,13.3)
I get the right results when I calculate: ks.test(xi,pnorm,11,1) Now the question: shouldn't I obtain the same or a very similar result if I commpare the sample and a calculated sample from the distribution?
p<- c(0.125, 0.250, 0.375, 0.500, 0.625, 0.750, 0.875, 0.9999) x <- qnorm(p,11,1)
ks.test(xi,x)
Why don't I?
Thanks for helping me!
Tonja

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