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Overcoming the multiple‐testing problem when testing randomness

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  • Neil H. Spencer

Abstract

Summary. We propose a new method for overcoming the problem of adjusting for the multiple‐testing problem in the context of testing random‐number generators. We suggest that it is to be used in conjunction with an existing method. More generally, the method can be useful in other situations where the multiple‐testing issue is encountered and the tests involved are not independent of each other, and their exact joint distribution is not readily available. The method makes use of the Mahalanobis distance and simulation. An example of its implementation is given by using data from a roulette wheel.

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  • Neil H. Spencer, 2009. "Overcoming the multiple‐testing problem when testing randomness," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 543-553, September.
    • Handle: RePEc:bla:jorssc:v:58:y:2009:i:4:p:543-553
    DOI: 10.1111/j.1467-9876.2009.00666.x
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    References listed on IDEAS

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    1. Kay I. Penny, 1996. "Appropriate Critical Values When Testing for a Single Multivariate Outlier by Using the Mahalanobis Distance," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(1), pages 73-81, March.
    2. Keren, Gideon & Lewis, Charles, 1994. "The Two Fallacies of Gamblers: Type I and Type II," Organizational Behavior and Human Decision Processes, Elsevier, vol. 60(1), pages 75-89, October.
    3. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
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    Cited by:

    1. Frey, Jesse, 2012. "Testing for positive evidence of equally likely outcomes," Journal of Multivariate Analysis, Elsevier, vol. 103(1), pages 48-57, January.

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