Is the kolmogorov-smirnov test valid on both continuous and discrete data?
I don't think so, and the example below helped me understand why.
A suggestion on testing the discrete data would be appreciated.
Thanks,
a <- rnorm(1000, 10, 1);a # normal distribution a
b <- rnorm(1000, 12, 1.5);b # normal distribution b
c <- rnorm(1000, 8, 1);c # normal distribution c
d <- rnorm(1000, 12, 2.5);d # normal distribution d
par(mfrow=c(2,2), las=1)
ahist<-hist(a, breaks=1:25, prob=T, ylim=c(0,0.4));box() # histograms of a
bhist<-hist(b, breaks=1:25, prob=T, ylim=c(0,0.4));box() # histograms of b
chist<-hist(c, breaks=1:25, prob=T, ylim=c(0,0.4));box() # histograms of c
dhist<-hist(d, breaks=1:25, prob=T, ylim=c(0,0.4));box() # histograms of d
ks.test(c(a,b), c(c,d), alternative="two.sided") # kolmogorov-smirnov on
continuous data
ks.test(c(ahist$density, bhist$density), c(chist$density, dhist$density),
alternative="two.sided") # kolmogorov-smirnov on discrete data
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