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Villas-Boas, SB, Fu, Q and Judge, G (2017). Benford’s law and the FSD distribution of economic behavioral micro data . Physica A: Statistical Mechanics and its Applications Volume 486, pp. 711-719.

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Anderson, KM, Dayaratna, K, Gonshorowski, D and Miller, SJ (2022). A New Benford Test for Clustered Data with Applications to American Elections. Stats 5(3), pp. 841–855. DOI:10.3390/stats5030049 . View Complete Reference Online information Works that this work references No Bibliography works reference this work
Becker, T, Burt, D, Corcoran, TC, Greaves-Tunnell, A, Iafrate, JR, Jing, J, Miller, SJ, Porfilio, JD, Ronan, R, Samranvedhya, J, Strauch, FW and Talbut, B (2018). Benford's Law and Continuous Dependent Random Variables. Annals of Physics 388, pp. 350–381. DOI:10.1016/j.aop.2017.11.013. View Complete Reference Online information Works that this work references Works that reference this work
Branets, S (2019). Detecting money laundering with Benford’s law and machine learning . Masters Thesis, University of Tartu. View Complete Reference Online information Works that this work references Works that reference this work
Capalbo, F, Galati, L, Lupi, C and Smarra, M (2023). Local elections and the quality of financial statements in municipally owned entities: A Benford analysis. Chaos, Solitons and Fractals 173 p. 113752. DOI:10.1016/j.chaos.2023.113752. View Complete Reference Online information Works that this work references Works that reference this work
Fang, X, Miller, SJ, Sun, M and Verga, A (2023). Generalized Continuous and Discrete Stick Fragmentation and Benford’s Law. Preprint arXiv:2309.00766 [math.PR]; last accessed September 12, 2023. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Fang, X, Miller, SJ, Sun, M and Verga, A (2024). Benford’s Law and Random Integer Decomposition with Congruence Stopping Condition. Preprint. View Complete Reference Online information Works that this work references No Bibliography works reference this work
González, F (2019). Detecting Anomalous Data in Household Surveys: Evidence for Argentina. Journal of Social and Economic Statistics 8(2), pp. 1-10. DOI:10.2478/jses-2019-0001. View Complete Reference Online information Works that this work references No Bibliography works reference this work
González, F (2020). Self-reported income data: are people telling the truth?. To appear in Journal of Financial Crime. DOI:10.1108/JFC-08-2019-0113. View Complete Reference Online information Works that this work references Works that reference this work
Jošić , H and Žmuk, B (2020). The Application of the Law of Anomalous Numbers on Global Food Prices in Examining Psychological Pricing Strategies. Journal of International Food & Agribusiness Marketing, pp. 1-16. DOI:10.1080/08974438.2020.1796880 . View Complete Reference Online information Works that this work references Works that reference this work
Kaiser, M (2019). Benford’s Law As An Indicator Of Survey Reliability—Can We Trust Our Data?. Journal of Economic Surveys Vol. 00, No. 0, pp. 1–17. DOI:10.1111/joes.12338. View Complete Reference Online information Works that this work references Works that reference this work
Mahasuar, K (2021). Lies, damned lies, and statistics: The uncertainty over COVID-19 numbers in India. Knowledge and Process Management, pp. 1– 8. DOI:10.1002/kpm.1685. View Complete Reference Online information Works that this work references Works that reference this work
Martínez-Sánchez, F (2021). Tracking The Price of Almonds in Spain. Journal of Competition Law & Economics, nhab002. DOI:10.1093/joclec/nhab002. View Complete Reference Online information Works that this work references Works that reference this work
Ramos, PCR (2021). Lei de Benford: uma Integração no Trabalho de Auditoria [Benford Law - An Integration in the Audit Work]. Masters thesis, Universidade de Brasília, Brasília. POR View Complete Reference Online information Works that this work references Works that reference this work