Institute of Mathematical Statistics Collections
On Detecting Fake Coin Flip Sequences
Classification of data as true or fabricated has applications in fraud detection and verification of data samples. In this paper, we apply nonlinear filtering to a simplified fraud-detection problem: classifying coin flip sequences as either real or faked. On the way, we propose a method for generating Bernoulli variables with given marginal probabilities and pair-wise covariances. Finally, we present the empirical performance of the classification algorithm.
First available in Project Euclid: 28 January 2009
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Copyright © 2008, Institute of Mathematical Statistics
Kouritzin, Michael A.; Newton, Fraser; Orsten, Sterling; Wilson, Daniel C. On Detecting Fake Coin Flip Sequences. Markov Processes and Related Topics: A Festschrift for Thomas G. Kurtz, 107--122, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2008. doi:10.1214/074921708000000336. https://projecteuclid.org/euclid.imsc/1233152938
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