Estimating the Proportion of True Null Hypotheses in Nonparametric Exponential Mixture Model with Appication to the Leukemia Gene Expression Data

DOI10.1080/03610918.2011.611308zbMath1271.62166OpenAlexW2086675723MaRDI QIDQ3168372

Xiaoxia Wu, Hong Zhang, Hua-Ling Zhao, Hanfeng Chen

Publication date: 30 October 2012

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.611308

zbMATH Keywords

EM algorithmmultiple testingFDRnonparametric mixture modelAitken's acceleration ruleCNM algorithm

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Paired and multiple comparisons; multiple testing (62J15)

Related Items (2)

Estimating the proportion of true null hypotheses in multiple testing problems ⋮ Symmetric directional false discovery rate control

Cites Work

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• The geometry of mixture likelihoods: A general theory
• The positive false discovery rate: A Bayesian interpretation and the \(q\)-value
• Parametric and Nonparametric FDR Estimation Revisited
• A Direct Approach to False Discovery Rates
• On Fast Computation of the Non-Parametric Maximum Likelihood Estimate of a Mixing Distribution
• Statistical significance for genomewide studies
• Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data
• Large-Scale Simultaneous Hypothesis Testing
• Identifiability of Mixtures

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