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Joenssen, DW (2014). Testing for Benford's Law: A Monte Carlo Comparison of Methods. Preprint available at SSRN: https://ssrn.com/abstract=2545243; last accessed Mar 24, 2019 .

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Cerasa, A (2022). Testing for Benford’s Law in very small samples: Simulation study and a new test proposal. PLoS ONE 17(7), pp. e0271969. DOI:10.1371/journal.pone.0271969. View Complete Reference Online information Works that this work references Works that reference this work
Cerqueti, R and Lupi, C (2022). Severe testing of Benford’s law. Preprint arXiv:2202.05237 [stat.ME]; last accessed February 21, 2022. View Complete Reference Online information Works that this work references Works that reference this work
Ducharme, RG, Kaci, S and Vovor-Dassu ,C (2020). Smooths Tests of Goodness-of-fit for the Newcomb-Benford distribution. Preprint: arXiv:2003.00520v1 [math.ST]. Published in Mathématiques appliquées et stochastiques, 3(1). FRE View Complete Reference Online information Works that this work references Works that reference this work
Pröger, L, Griesberger, P, Hackländer, K, Brunner, N and Kühleitner, M (2021). Benford’s Law for Telemetry Data of Wildlife. Stats 4(4), pp. 943–949. DOI:10.3390/ stats4040055. View Complete Reference Online information Works that this work references Works that reference this work
Sadaf, R (2017). Advanced Statistical Techniques For Testing Benford'S Law. Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pp. 229-238. View Complete Reference Online information Works that this work references Works that reference this work
Silva, AdeA and Gouvêa, MA (2023). Study on the effect of sample size on type I error, in the first, second and first-two digits excessmad tests. International Journal of Accounting Information Systems 48, p. 100599. DOI:10.1016/j.accinf.2022.100599. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Vovor-Dassu, KC (2021). Tests d'adéquation à la loi de Newcomb-Benford comme outils de détection de fraudes. PhD Thesis L’Universite de Montpellier. DOI:10.13140/RG.2.2.12559.25764. FRE View Complete Reference Online information Works that this work references No Bibliography works reference this work