Varma, TNP and Khan, DA (2012). Fraud Detection in Supply Chain using Benford Distribution. International Journal of Research in Management 2(5), pp. 90-96.
This work cites the following items of the Benford Online Bibliography:
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572.
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Berger, A and Hill, TP (2007). Newton’s method obeys Benford’s law. American Mathematical Monthly 114 (7), pp. 588-601. ISSN/ISBN:0002-9890.
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Cho, WKT and Gaines, BJ (2007). Breaking the (Benford) law: Statistical fraud detection in campaign finance. American Statistician 61(3), pp. 218-223. ISSN/ISBN:0003-1305. DOI:10.1198/000313007X223496.
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Durtschi, C, Hillison, W and Pacini, C (2004). The effective use of Benford’s law to assist in detecting fraud in accounting data. Journal of Forensic Accounting 1524-5586/Vol. V, pp. 17-34.
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Kailasam, L (2011). Benford Distribution - An Effective Audit Tool. The Chartered Accountant, November 2011, pp. 716-720.
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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.
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Roukema, BF (2009). Benford's Law Anomalies in the 2009 Iranian presidential election. preprint arXiv:0906.2789.
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Saville, A (2006). Using Benford's law to detect data error and fraud: an examination of companies listed on the Johannesburg Stock Exchange. South African Journal of Economic and Management Sciences 9(3), 341-354. ISSN/ISBN:1015-8812.
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Thomas, JK (1989). Unusual Patterns in Reported Earnings. Accounting Review 64(4), 773-787. ISSN/ISBN:0001-4826.
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Varian, HR (1972). Benford’s law. The American Statistician 26(3), 65-66. DOI:10.1080/00031305.1972.10478934.
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