Description Usage Arguments Value Constraints See Also Examples
Perform a one- or two-sample Kolmogorov-Smirnov test.
1 2 |
x |
a FLVector of data values. |
y |
either a FLVector 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. |
A list with class "htest".
As of now only supports normal disctribution, alternative and exact isn't supported for FL objects
ks.test
for corresponding R function reference.
1 2 3 4 5 6 7 8 9 10 11 12 13 | set.seed(100)
p <- as.FLVector(rnorm(50))
q <- as.FLVector(runif(30))
ks.test(p, y= "NORMAL" , mean=0, sd=1)
## One sample K-S test.
res <- ks.test(p, q)
## Two sample K-S Test.
#If y is a FLVector, a two-sample test of the null hypothesis that x and y were drawn from the
#same continuous distribution is performed. Alternatively, y can be a character string naming
#a continuous (cumulative) distribution function, or such a function. In this case, a one-sample
#test is carried out of the null that the distribution function which generated x is distribution
#y with parameters.
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