Effects of statistical dependence on multiple testing under a hidden Markov model
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Publication:2429937
DOI10.1214/10-AOS822zbMath1209.62192arXiv0904.1551MaRDI QIDQ2429937
Publication date: 5 April 2011
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0904.1551
Hypothesis testing in multivariate analysis (62H15) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Markov processes: hypothesis testing (62M02)
Related Items (3)
A double application of the Benjamini-Hochberg procedure for testing batched hypotheses ⋮ Bayesian hidden Markov models for dependent large-scale multiple testing ⋮ False discovery variance reduction in large scale simultaneous hypothesis tests
Cites Work
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- A simple proof of Kaijser's unique ergodicity result for hidden Markov \(\alpha\)-chains
- A limit theorem for partially observed Markov chains
- Exponential stability for nonlinear filtering
- Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
- Stability of nonlinear filters in nonmixing case
- The control of the false discovery rate in multiple testing under dependency.
- False discovery rate control with multivariate \(p\)-values
- Basic properties of the projective product with application to products of column-allowable nonnegative matrices
- Exponential forgetting and geometric ergodicity in hidden Markov models
- Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models
- On a role of predictor in the filtering stability
- On false discovery control under dependence
- Properties of higher criticism under strong dependence
- False discovery and false nondiscovery rates in single-step multiple testing procedures
- Ergodicity of hidden Markov models
- Large-Scale Multiple Testing under Dependence
- Lyapunov Exponents for Finite State Nonlinear Filtering
- Risk-Sensitive Control of Finite State Machines on an Infinite Horizon II
- Empirical Bayes Analysis of a Microarray Experiment
- Optimal Sample Size for Multiple Testing
- Asymptotic Stability of the Wonham Filter: Ergodic and Nonergodic Signals
- 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
- Asymptotics of the maximum likelihood estimator for general hidden Markov models
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