KS test and theoretical distribution
On Thu, 6 Oct 2011, francogrex wrote:
x <- runif(100) y <- runif(100) ks.test(x,y)
Two-sample Kolmogorov-Smirnov test
data: x and y
D = 0.11, p-value = 0.5806
alternative hypothesis: two-sided
ok I expected that, but:
ks.test(runif(100), "runif")
One-sample Kolmogorov-Smirnov test
data: runif(100)
D = 0.9106, p-value < 2.2e-16
alternative hypothesis: two-sided
How come?
Because you didn't read the docs, or didn't follow them, or mistyped. The
docs say
y: either a numeric vector of data values, or a character string
naming a cumulative distribution function or an actual
cumulative distribution function such as 'pnorm'. Only
continuous CDFs are valid.
So you would want
ks.test(runif(100), "punif")
Best,
Z
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