This work cites the following items of the Benford Online Bibliography:
Abrantes-Metz, RM, Kraten, M, Metz, AD and Seow, G (2012). Libor Manipulation?. Journal of Banking & Finance 36(1), pp. 136-150. ISSN/ISBN:0378-4266. DOI:10.1016/j.jbankfin.2011.06.014. | ||||
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. | ||||
Cajueiro, D (2016). Existem formas de detectar fraudes em bases de dados?. Posted on Prorum.com February 5, 2016; last accessed November 17, 2020. POR | ||||
Hales, DN, Sridharan, V, Radhakrishnan, A, Chakravorty, SS and Sihad, SM (2008). Testing the accuracy of employee-reported data: An inexpensive alternative approach to traditional methods. European Journal of Operational Research 189(3), pp. 583-593. | ||||
Kopczewski, T and Okhrimenko, I (2019). Playing with Benfordâ€™s Law. E-print posted on http://www.nbp.pl/badania/seminaria/8ii2019.pdf; last accessed June 6, 2019. | ||||
Newcomb, S (1881). Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics 4(1), pp. 39-40. ISSN/ISBN:0002-9327. DOI:10.2307/2369148. | ||||
Nigrini, MJ (2012). Benford's Law: Applications for Forensic Accounting, Auditing, and Fraud Detection . John Wiley & Sons: Hoboken, New Jersey. ISSN/ISBN:978-1-118-15285-0. DOI:10.1002/9781119203094. | ||||
Sarkar, T (2018). What is Benfordâ€™s Law and why is it important for data science?. Posted on: towardsdatascience.com, last accessed September 3, 2019. | ||||
Suh, I and Headrick, TC (2010). A comparative analysis of the bootstrap versus traditional statistical procedures applied to digital analysis based on Benford's Law. Journal of Forensic and Investigative Accounting 2(2), 2010, 144-175. |