Multiple testing under dependence via graphical models
نویسندگان
چکیده
منابع مشابه
Multiple Testing under Dependence via Graphical Models
Large-scale multiple testing tasks often exhibit dependence. Leveraging the dependence between individual tests is still one challenging and important problem in statistics. With recent advances in graphical models, it is feasible to use them to capture the dependence among multiple hypotheses. We propose a multiple testing procedure which is based on a Markov-random-field-coupled mixture model...
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It has been shown that graphical models can be used to leverage the dependence in large-scale multiple testing problems with significantly improved performance (Sun & Cai, 2009; Liu et al., 2012). These graphical models are fully parametric and require that we know the parameterization of f1 - the density function of the test statistic under the alternative hypothesis. However in practice, f1 i...
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Large-scale multiple testing tasks often exhibit dependence. Leveraging the dependence between individual tests is still one challenging and important problem in statistics. With recent advances in graphical models, it is feasible to use them to capture the dependence among multiple hypotheses. We propose a multiple testing procedure which is based on a Markov-randomfield-coupled mixture model....
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The paper considers the problem of multiple testing under dependence in a compound decision theoretic framework. The observed data are assumed to be generated from an underlying two-state hidden Markov model.We propose oracle and asymptotically optimal datadriven procedures that aim to minimize the false non-discovery rate FNR subject to a constraint on the false discovery rate FDR. It is shown...
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Large-scale multiple testing tasks often exhibit dependence, and leveraging the dependence between individual tests is still one challenging and important problem in statistics. With recent advances in graphical models, it is feasible to use them to perform multiple testing under dependence. We propose a multiple testing procedure which is based on a Markov-random-field-coupled mixture model. T...
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ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2016
ISSN: 1932-6157
DOI: 10.1214/16-aoas956