This work is cited by the following items of the Benford Online Bibliography:
Ausloos, M, Ficcadenti, V, Dhesi, G and Shakeel, M (2021). Benford’s laws tests on S&P500 daily closing values and the corresponding daily log-returns both point to huge non-conformity. 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 log-returns both point to huge non-conformity. Preprint arXiv:2104.07962 [q-fin.ST]; last accessed April 30, 2021. To appear in: Physica A: Statistical Mechanics and its Applications, 574. DOI:10.1016/j.physa.2021.125969. | ||||
Branets, S (2019). Detecting money laundering with Benford’s law and machine learning . Masters Thesis, University of Tartu. | ||||
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. | ||||
Cerqueti, R and Lupi, C (2021). Some New Tests of Conformity with Benford's Law. Stats 4(3), pp. 745-761. DOI:10.3390/stats4030044. | ||||
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. | ||||
Cerqueti, R, Maggi, M and Riccioni, J (2022). Statistical methods for decision support systems in finance: how Benford’s law predicts financial risk. Annals of Operations Research. DOI:10.1007/s10479-022-04742-z. | ||||
Cerqueti, R and Provenzano, D (2023). Benford's Law for economic data reliability: The case of tourism flows in Sicily. Chaos, Solitons & Fractals 173, p. 113635. DOI:10.1016/j.chaos.2023.113635. | ||||
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 | ||||
Ileanu, B-V (2021). Time Lag Evidence of Anti-Abortion Decree and Perturbation of Births Distribution. A Benford Law Approach. Preprint arXiv:2106.15520 [physics.soc-ph]; last accessed July 30, 2021. | ||||
Ileanu, B-V, Ausloos, M, Herteliu, C and Cristescu, MP (2019). Intriguing behavior when testing the impact of quotation marks usage in Google search results. Quality & Quantity 53(5), pp. 2507-2519. DOI:10.1007/s11135-018-0771-0. | ||||
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. | ||||
Luty, P (2022). Tax Avoidance, Fraud Detection and Related Accounting Issues - Insights from the Visegrad Group Countries. Publishing House of Wroclaw University of Economics and Business, pp. 99-117. ISSN/ISBN:978-83-7695-970-2. DOI:10.15611/2022.971.9. | ||||
Luty, P and Costa, R (2022). Benford's Law in the Analysis of Inventories of Portuguese Companies. International Journal of Business Innovation 1(4), p. e30282. DOI:10.34624/ijbi.v1i4.30282. | ||||
Martínez-Sánchez, F (2021). Tracking The Price of Almonds in Spain. Journal of Competition Law & Economics, nhab002. DOI:10.1093/joclec/nhab002. | ||||
Pavlović, V, Knežević, G, Joksimović, M and Joksimović, D (2019). Fraud Detection in Financial Statements Applying Benford's Law with Monte Carlo Simulation. Acta oeconomica 69(2), pp.217-239. DOI:10.1556/032.2019.69.2.4. | ||||
Riccioni, J and Cerqueti, R (2018). Regular paths in financial markets: Investigating the Benford’s law. Chaos, Solitons and Fractals 107, pp. 186-194. DOI:10.1016/j.chaos.2018.01.008. | ||||
Shi, J, Ausloos, M and Zhu, T (2018). Benford's law is the first significant digit and distribution distances for testing the reliability of financial reports in developing countries. Physica A: Statistical Mechanics and its Applications 492(1), pp. 878-888. DOI:10.1016/j.physa.2017.11.017. | ||||
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 | ||||
Wang, D, Chen, F, Mao, J, Liu, N and Rong, F (2022). Are the official national data credible? Empirical evidence from statistics quality evaluation of China's coal and its downstream industries . Energy Economics, p. 106310. DOI:10.1016/j.eneco.2022.106310. |