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On Detecting Fake Coin Flip Sequences
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- Author(s) / Creator(s)
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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.
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- Date created
- 2008
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- Subjects / Keywords
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- Type of Item
- Conference/Workshop Presentation
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- License
- © 2008. Institute of Mathematical Statistics. This version of this article is open access and can be downloaded and shared. The original author(s) and source must be cited.