Math @ Duke

Publications [#47824] of Mark Huber
Papers Published
 M. Huber, Y. Chen, I. Dinwoodie, A. Dobra, and M. Nicholas, Monte Carlo algorithms for HardyWeinberg proportions,
Biometrics, vol. 62 no. 1
(March, 2006),
pp. 4953, Blackwell Synergy
(last updated on 2006/06/15)
Abstract: The HardyWeinberg law is among the most important principles in the study of biological systems (Crow, 1988, Genetics 119, 473476). Given its importance, many tests have been devised to determines whether a finite population folows HardyWeinberg proportions. Because asymptotic tests can fail, Guo and Thompson (1992, Biometrics 48, 361372) devloped an exact test; unfortunately, the Monte Carlo method they proposed to evaluate their test has a running time that grows linearly in the size of the population N. Here, we propose a new algorithm whose expected running time is linear in the size of the table produced, and completely independent of N. In practice, this new algorithm can be considerably faster than the original method.


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