Kolmogorov–Smirnov test KS can be done for the single variable as
x <- rnorm(50)
ks.test(x, "pnorm", mean=mean(x), sd=sd(x))
Results:
One-sample Kolmogorov-Smirnov test
data: x D = 0.057841, p-value = 0.9927 alternative hypothesis: two-sided
How can I compute the weighted KS for single variable as well? I appreciate your suggestions. Thanks!
library(Ecume)
ks_test(x, y,thresh = .001)
I wanted to reproduce the test results of modified KS test of this paper on Jarque –Bera Test and its Competitors for Testing Normality – A Power Comparison.
Jarque –Bera Test and its Competitors for Testing Normality – A Power Comparison