Grabski, S (2010). Discussion of 'Data mining journal entries for fraud detection: An exploratory study'. International Journal of Accounting Information Systems, Vol. 11, No. 3, pp. 182–185.
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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Boyle, J (1994). An Application of Fourier Series to the Most Significant Digit Problem. American Mathematical Monthly 101(9), pp. 879-886. ISSN/ISBN:0002-9890. DOI:10.2307/2975136.
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Debreceny, RS and Gray, GL (2010). Data mining journal entries for fraud detection: An exploratory study. International Journal of Accounting Information Systems, Vol. 11, No. 3, pp. 157–181. DOI:10.1016/j.accinf.2010.08.001.
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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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Nigrini, MJ and Miller, SJ (2009). Data Diagnostics Using Second-Order Tests of Benford's Law. Auditing: A Journal of Practice & Theory 28(2), pp. 305-324. DOI:10.2308/aud.2009.28.2.305
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Nigrini, MJ and Mittermaier, LJ (1997). The use of Benford's Law as an aid in analytical procedures. Auditing - A Journal of Practice & Theory 16(2), 52-67. ISSN/ISBN:0278-0380.
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