This work is cited by the following items of the Benford Online Bibliography:
Arshadi, L and Jahangir, AH (2014). Benford's law behavior of Internet traffic. Journal of Network and Computer Applications, Volume 40, April 2014, pp. 194–205. ISSN/ISBN:1084-8045. DOI:10.1016/j.jnca.2013.09.007. | ||||
Avcı, O and Demirci, Z (2016). Benford Kanunu’nun Vergi Denetiminde Kullanımı Ve Bir Örnek Uygulama [Use of Benford's Law in Tax Auditing and A Sample Application] . İnsan ve Toplum Bilimleri Araştırması Dergisi 5(7), pp. 2232-2246. DOI:10.15869/itobiad.260262. TUR | ||||
Badal-Valero, E, Alvarez-Jareño, JA and Pavía, JM (2018). Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case. Forensic Science International 282, pp. 24-34. DOI:10.1016/j.forsciint.2017.11.008. | ||||
Barabesi, L, Cerasa, A, Cerioli, A and Perrotta, D (2018). Goodness-of-fit testing for the Newcomb-Benford law with application to the detection of customs fraud. Journal of Business & Economic Statistics 36(2), pp. 346-358. DOI:10.1080/07350015.2016.1172014. | ||||
Branets, S (2019). Detecting money laundering with Benford’s law and machine learning . Masters Thesis, University of Tartu. | ||||
Brock, T (2014). Benford’s law and elections – part 2. Posted on Datatodisplay.com blog; last accessed April 25, 2019. | ||||
Cerioli, A, Barabesi, L, Cerasa, A, Menegatti, M and Perrotta, D (2019). Newcomb-Benford law and the detection of frauds in international trade. Proceedings of the National Academy of Sciences 116(1), pp. 106-115. DOI:10.1073/pnas.1806617115. | ||||
Fonseca, PMT da (2016). Digit analysis using Benford's Law: A Bayesian approach. Masters Thesis, ISEG - Instituto Superior de Economia e Gestão, Lisbon School of Economics & Management, Portugal. | ||||
Huang, Y, Niu, Z and Yang, C (2020). Testing firm-level data quality in China against Benford’s Law. Economics Letters 192, 109182. DOI:10.1016/j.econlet.2020.109182. | ||||
Jiménez, R and Hidalgo, M (2014). Forensic Analysis of Venezuelan Elections during the Cha ́vez Presidency. PLOS ONE 9(6), pp. 1-18. DOI:10.1371/journal.pone.0100884. | ||||
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 . DOI:10.2139/ssrn.2545243. | ||||
Joksimović, D, Knežević, G, Pavlović, V, Ljubić, M and Surovy, V (2017). Some Aspects of the Application of Benford’s Law in the Analysis of the Data Set Anomalies. In: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling. New York: Nova Science Publishers, pp. 85–120. ISSN/ISBN:978-1-53610-566-7. | ||||
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 . | ||||
Lacasa, L (2019). Newcomb–Benford law helps customs officers to detect fraud in international trade. Proceedings of the National Academy of Sciences 116(1), pp. 11-13. DOI:10.1073/pnas.1819470116. | ||||
Lacasa, L and Fernández-Gracia, J (2019). Election Forensics: Quantitative methods for electoral fraud detection. Forensic Science International 294, pp. e19-e22. DOI:10.1016/j.forsciint.2018.11.010. | ||||
Li, F, Han, S, Zhang, H, Ding, J, Zhang, J and Wu, J (2019). Application of Benford’s law in Data Analysis. Journal of Physics: Conference Series 1168, pp. 032133. DOI:10.1088/1742-6596/1168/3/032133. | ||||
Mack, V (2016). The Fingerprints of Fraud: An In-depth Study of Election Forensics with Digit Tests. PhD Thesis, Universitat Konstanz. | ||||
Mainusch, NM (2020). On Benford's law - Computing a Bayes factor with the Savage-Dickey method to quantify conformance of numerical data to Benford's law. Bachelor's Thesis, University of Osnabrueck, Institute of Cognitive Science, Germany. | ||||
Mebane, WR Jr (2012). Second-digit Tests for Voters’ Election Strategies and Election Fraud. Prepared for presentation at the 2012 Annual Meeting of the Midwest Political Science Association, Chicago, April 12–15; last accessed Apr 11, 2019. | ||||
Mebane, WR Jr (2013). Election Forensics: The Meanings of Precinct Vote Counts’ Second Digits. Prepared for presentation at the 2013 Summer Meeting of the Political Methodology Society, University of Virginia, July 18–20. | ||||
Mebane, WR Jr and Kent, T (2013). Second digit implications of voters’ strategies and mobilizations in the United States during the 2000s. Proceedings of the 2013 Annual Meeting of the Midwest Political Science Association, Chicago, IL, April 11–14. | ||||
Mebane, WR Jr and Klaver, J (2015). Election Forensics: Strategies versus Election Frauds in Germany. Prepared for presentation at the 2015 Annual Conference of the European Political Science Association, Vienna, Austria, June 25–27. | ||||
Medzihorsky, J (2015). Election Fraud: A Latent Class Framework for Digit-Based Tests. Political Analysis 23(4), pp. 506-517. DOI:10.1093/pan/mpv021. | ||||
Miller, SJ (ed.) (2015). Benford's Law: Theory and Applications. Princeton University Press: Princeton and Oxford. ISSN/ISBN:978-0-691-14761-1. | ||||
Morag, S and Salmon-Divon, M (2019). Characterizing Human Cell Types and Tissue Origin Using the Benford Law. Cells 8(9), p. 1004. DOI:10.3390/cells8091004. | ||||
Pierzgalski, M (2018). Odkrywanie fałszerstw wyborczych a „prawo” Benforda [Discovering Election Fraud and Benford’s “Law”]. Preprint, last accessed Apr 25, 2019. DOI:10.14746/ssp.2018.1.7. POL | ||||
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. |