Ausloos, M, Ficcadenti, V, Dhesi, G and Shakeel, M (2021). Benford’s laws tests on S&P500 daily closing values and the corresponding daily logreturns both point to huge nonconformity. Physica A: Statistical Mechanics and its Applications 574, pp. 125969. DOI:10.1016/j.physa.2021.125969.





Ausloos, M, Ficcadenti, V, Dhesi, G and Shakeel, M (2021). Benford's laws tests on S&P500 daily closing values and the corresponding daily logreturns both point to huge nonconformity. Preprint arXiv:2104.07962 [qfin.ST]; last accessed April 30, 2021. To appear in: Physica A: Statistical Mechanics and its Applications, 574. DOI:10.1016/j.physa.2021.125969.





Awad, MM (2022). Evaluation of COVID19 Reported Statistical Data Using Cooperative Convolutional Neural Network Model (CCNN). COVID 2(5), pp. 674–690. DOI:10.3390/covid2050051.





Barabesi, L, Cerasa, A, Cerioli, A and Perotta, D (2021). A combined test of the Benford Hypothesis With Antifraud Applications. Proceedings of 13th Scientific Meeting of the Classification and Data Analysis Group, Florence, September 911. STAMPA, pp. 256259. DOI:10.36253/9788855183406.





Barabesi, L, Cerasa, A, Cerioli, A and Perrotta, D (2021). On characterizations and tests of Benford’s law. Journal of the American Statistical Association. DOI:10.1080/01621459.2021.1891927.





Barabesi, L, Cerioli, A and Di Marzio, M (2023). Statistical models and the Benford hypothesis: a unified framework. TEST. DOI:10.1007/s1174902300881y.





Barabesi, L, Cerioli, A and Perrotta, D (2021). Forum on Benford’s law and statistical methods for the detection of frauds. Statistical Methods & Applications 30, pp. 767–778. DOI:10.1007/s10260021005880.





BeneditoNunes, AM, Gamper, J, Chapman, SC, Friel, M and Gjerloev, JW (2023). NewcombBenford Law characterization of solar wind magnetic field and geomagnetic indices. Posted on Authorea; last accessed April 29, 2023. DOI:10.22541/essoar.168121593.35845953/v1.





BeneditoNunes, AM, Gamper, J, Chapman, SC, Friel, M and Gjerloev, JW (2023). NewcombBenford Law as a generic flag for changes in the derivation of longterm solar terrestrial physics timeseries. RAS Techniques and Instruments, pp. rzad041. DOI:10.1093/rasti/rzad041.





Burgos, A and Santos, A (2021). The Newcomb–Benford law: Scale invariance and a simple Markov process based on it (Previous title: The Newcomb–Benford law: Do physicists use more frequently the key 1 than the key 9?). Preprint arXiv:2101.12068 [physics.popph]; last accessed August 8, 2022; Published Am. J. Phys. 89, pp. 851861.





Cangiotti, N and Sensi, M (2022). Benford’s Law: A NumberTheoretical Perspective . Palestine Journal of Mathematics 11(3), pp. 379–385.





Cerqueti, R and Maggi, M (2021). Data validity and statistical conformity with Benford’s Law. Chaos, Solitons & Fractals 144, p. 110740
. DOI:10.1016/j.chaos.2021.110740.





Dutta, A, Voumik, LC, Kumarasankaralingam, L, Rahaman, A and Zimon, G (2023). The Silicon Valley Bank Failure: Application of Benford’s Law to Spot Abnormalities and Risks. Risks 11(7), p. 120. DOI:10.3390/risks11070120.





Filho, TMR, Mendes, JFF, Lucio, ML and Moret, MA (2022). Reliability of COVID19 data and government policies. Preprint arXiv:2208.11226 [physics.socph]; last accessed August 31, 2022.





Hill, TP (2020). A Widespread Error in the Use of Benford's Law to Detect Election and Other Fraud. Preprint arXiv:2011.13015 [math.PR]; posted November 25, 2020. Last accessed November 30, 2020.





Huber, H (2023). Explanations of Benford’s Law. Undergraduate research paper, William and Mary.





Hulme, PE, Ahmed, DA, Haubrock, PJ, Kaiser, BA, Kourantidou, M, Leroy, B and McDermott, SM (2023). Widespread imprecision in estimates of the economic costs of invasive alien species worldwide. Science of the Total Environment, pp. 167997. DOI:10.1016/j.scitotenv.2023.167997.





Mucko, P and Adamczyk, A (2023). Does the bankrupt cheat? Impact of accounting manipulations on the effectiveness of a bankruptcy prediction. PLoS ONE 18(1), e0280384. ISSN/ISBN:19326203. DOI:10.1371/journal.pone.0280384.





Pain, JC and Croset, P (2023). Checking the reliability of opacity databases. Preprint arXiv:2304.02469 [physics.atomph]; last accessed April 19, 2023.





Parker, MC and Jeynes, C (2023). A Maximum Entropy Resolution to the Wine/Water Paradox. Posted on Preprints.org 2023061551; last access June 28. 2023. DOI:10.20944/preprints202306.1551.v1.




