Small Samples’ Permille Cramér–Von Mises Statistic Critical Values for Continuous Distributions as Functions of Sample Size

Lorentz Jäntschi ()
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Lorentz Jäntschi: Department of Physics and Chemistry, Technical University of Cluj-Napoca, 103-105 Muncii Blvd., 400641 Cluj-Napoca, Romania

Data, 2025, vol. 10, issue 11, 1-7

Abstract: Along with other order statistics, the Cramér–von Mises (CM) statistic can assess the goodness of fit. CM does not have an explicit formula for the cumulative distribution function and the alternate way is to obtain its critical value from a Monte Carlo (MC) experiment. A high resolution experiment was deployed to generate a large amount of data resembling CM. Twenty-one repetitions of the experiment were conducted, and in each case, critical values of the CM statistic were obtained for all permilles and sample sizes from 2 to 30. The raw data presented here can serve to interpolate and extract probabilities associated with CM statistic directly, or to obtain a mathematical model for the bivariate dependence.

Keywords: Cramér–von Mises statistic; Monte–Carlo simulation (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jdataj:v:10:y:2025:i:11:p:181-:d:1787994

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