sarkadi.unif.test: Sarkadi-Kosik test for uniformity
Description
Performs Sarkadi-Kosik test for the hypothesis of uniformity.
Usage
sarkadi.unif.test(x, nrepl=2000)
Arguments
x
a numeric vector of data values.
nrepl
the number of replications in Monte Carlo simulation.
Value
A list with class "htest" containing the following components:
statisticthe value of the Sarkadi-Kosik statistic.
p.valuethe p-value for the test.
methodthe character string "Sarkadi-Kosik test for uniformity".
data.namea character string giving the name(s) of the data.
Details
The Sarkadi-Kosik test for uniformity is based on the following statistic:
$$J = n^2\sum_{i=1}^{n}{\left( \frac{x_i-\frac{i}{n+1}}{i\left(n-i+1\right)} \right)^2}-n\left(\sum_{i=1}^{n}{\frac{x_i-\frac{i}{n+1}}{i\left(n-i+1\right)}} \right)^2.$$
The p-value is computed by Monte Carlo simulation.
References
Kosik P., Sarkadi K. A new goodness-of-fit test // Proc. of 5-th Pannonian Symp. of Math. Stat., Visegrad, Hungary, 20 24 May, 1985. P. 267 272.