Campanelli, L (2022)

Tuning up the Kolmogorov-Smirnov test for testing Benford’s law

Preprint on ResearchGate.

ISSN/ISBN: Not available at this time. DOI: Not available at this time.

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Abstract: For moderately large and large numbers of data points (n ≥ 100) the Kolmogorov- Smirnov test is too conservative for testing Benford’s law. Moreover, the asymptotic cumulative distribution function of the Kolmogorov statistic shows unacceptable large deviations, up to about 35%, from the ones obtained in Monte Carlo simulations. Such deviations can be reduced to a level below 0.5% if an appropriate linear transformation of the argument of the Kolmogorov cumulative function is performed.

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Bibtex:
@misc{, author = {Leonardo Campanelli}, title = {Tuning up the Kolmogorov-Smirnov test for testing Benford’s law}, year = {2022}, url = {https://www.researchgate.net/publication/366356684}. }

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Reference Type: Preprint

Subject Area(s): Statistics

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