Buttorff, G (2008). Detecting fraud in America's gilded age. Working Paper No. 2, University of Iowa, Cal Tech/MIT Voting Technology Project.
This work is cited by the following items of the Benford Online Bibliography:
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Cantu, F and Saiegh, SM (2010). A Supervised Machine Learning Procedure to Detect Electoral Fraud Using Digital Analysis. Preprint posted on SSRN; last accessed August 5, 2021. DOI:10.2139/ssrn.1594406.
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Cantu, F and Saiegh, SM (2011). Fraudulent Democracy? An Analysis of Argentina’s Infamous Decade Using Supervised Machine Learning. Political Analysis 19 (4), pp. 409-433. DOI:10.1093/pan/mpr033.
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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.
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Pericchi, LR and Torres, DA (2011). Quick anomaly detection by the Newcomb-Benford law, with applications to electoral processes data from the USA, Puerto Rico and Venezuela. Statistical Science 26(4), pp. 502-16. DOI:10.1214/09-STS296.
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