Description Usage Arguments Details Value Author(s) References Examples
Performs Kolmogorov-Smirnov test for the hypothesis of uniformity, see Kolmogorov (1933).
1 | kolmogorov.unif.test(x, nrepl=2000,k=0)
|
x |
a numeric vector of data values. |
nrepl |
the number of replications in Monte Carlo simulation. |
k |
variant the criterion. |
The Kolmogorov-Smirnov test for uniformity is based on the following statistics:
D^+ = max_i≤ft(x_i-\frac{i}{n+1}\right),\quad D^- = max_i≤ft(\frac{i}{n+1}-x_i\right),\quad D = max(D^+,D^-).
The p-value is computed by Monte Carlo simulation.
A list with class "htest" containing the following components:
statistic |
the value of the Kolmogorov-Smirnov statistic. |
p.value |
the p-value for the test. |
method |
the character string "Kolmogorov-Smirnov test for uniformity". |
data.name |
a character string giving the name(s) of the data. |
Maxim Melnik and Ruslan Pusev
Kolmogorov A. (1933): Sulla determinazione empirica di una legge di distribuzione. — G. Ist. Ital. Attuari, vol. 4, pp. 83–91.
1 2 | kolmogorov.unif.test(runif(100,0,1))
kolmogorov.unif.test(runif(100,0.1,0.9))
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