Testing unilateral versus bilateral normal contamination
This letter proposes modeling a large collection of test statistics, such as may arise in microarray data analysis, using a mixture of three normal distributions: one with mean zero, one with nonnegative mean, and one with nonpositive mean. A convenient procedure is established for testing whether this three-component mixture may be reduced to a two-component mixture with one nonzero component mean.
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Volume (Year): 83 (2013)
Issue (Month): 1 ()
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- Hanfeng Chen & Jiahua Chen & John D. Kalbfleisch, 2001. "A modified likelihood ratio test for homogeneity in finite mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 19-29.
- Christopher Genovese & Larry Wasserman, 2002. "Operating characteristics and extensions of the false discovery rate procedure," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 499-517.
- Hongying Dai & Richard Charnigo, 2008. "Omnibus testing and gene filtration in microarray data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(1), pages 31-47.
- P. Li & J. Chen & P. Marriott, 2009. "Non-finite Fisher information and homogeneity: an EM approach," Biometrika, Biometrika Trust, vol. 96(2), pages 411-426.
- Allison, David B. & Gadbury, Gary L. & Heo, Moonseong & Fernandez, Jose R. & Lee, Cheol-Koo & Prolla, Tomas A. & Weindruch, Richard, 2002. "A mixture model approach for the analysis of microarray gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 1-20, March.
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