Large-Scale Multiple Testing under Dependence

DOI10.1111/j.1467-9868.2008.00694.xzbMath1248.62005OpenAlexW2074248125MaRDI QIDQ2920274

T. Tony Cai, Wenguang Sun

Publication date: 16 October 2012

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9868.2008.00694.x

zbMATH Keywords

hidden Markov modelsfalse discovery ratecompound decision problemmultiple testing under dependencelocal significance index

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric hypothesis testing (62F03) Compound decision problems in statistical decision theory (62C25)

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Uses Software

• alr3

Cites Work

• Unnamed Item
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• A constrained formulation of maximum-likelihood estimation for normal mixture distributions
• Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models
• Inference in hidden Markov models. I: Local asymptotic normality in the stationary case.
• Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics.
• The control of the false discovery rate in multiple testing under dependency.
• Multiple hypotheses testing and expected number of type I errors
• A stochastic process approach to false discovery control.
• On symmetric compound decision rules for dichotomies
• On false discovery control under dependence
• A hidden spatial-temporal Markov random field model for network-based analysis of time course gene expression data
• False discovery and false nondiscovery rates in single-step multiple testing procedures
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• False discovery control with p-value weighting
• Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control
• False Discovery Rates for Spatial Signals
• Hidden Markov chains and the analysis of genome structure
• Asymptotic Statistics
• Order estimation and sequential universal data compression of a hidden Markov source by the method of mixtures
• A Smooth Nonparametric Estimate of a Mixing Distribution Using Mixtures of Gaussians
• Penalized Maximum Likelihood Estimator for Normal Mixtures
• Empirical Bayes Analysis of a Microarray Experiment
• A Direct Approach to False Discovery Rates
• Operating Characteristics and Extensions of the False Discovery Rate Procedure
• Hidden Markov processes
• Correlation and Large-Scale Simultaneous Significance Testing
• Variance of the Number of False Discoveries
• Some Results on the Control of the False Discovery Rate under Dependence
• Large-Scale Simultaneous Hypothesis Testing
• Statistical Inference for Probabilistic Functions of Finite State Markov Chains
• Detecting differential gene expression with a semiparametric hierarchical mixture method