Multiple Testing under Dependence via Semiparametric Graphical Models
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Summary
This work proposes a novel semiparametric approach for multiple testing under dependence, which estimates f1 adaptively and outperforms classical procedures which assume independence and the parametric approaches which capture dependence.
- Type
- article
- Published
- 2014-06-21
- Cited by
- 4
- References
- 46
- Access
- Open access
- OpenAlex
- https://openalex.org/W166848722
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17730488
Keywords
Semiparametric model, Parametric statistics, Leverage (statistics), Semiparametric regression, Graphical model
References
- Statistical Analysis of Non-Lattice Data
- Multiple hypotheses testing and expected number of type I. errors
- Large-scale inference
- THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY
- Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies
- Finding the missing heritability of complex diseases
- Some Results on the Control of the False Discovery Rate under Dependence
- A Factor Model Approach to Multiple Testing Under Dependence
- Correlation and Large-Scale Simultaneous Significance Testing
- A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer
- False discovery control with p-value weighting
- Evaluation of Nyholt’s Procedure for Multiple Testing Correction
- Remarks on Some Nonparametric Estimates of a Density Function
- A general framework for multiple testing dependence
- Variance of the number of false discoveries
- False Discovery Rates for Spatial Signals
- Breast cancer survival is associated with telomere length in peripheral blood cells.
- A unified approach to false discovery rate estimation
- Some extensions of score matching
- Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics
Cited by
- Analyse bioinformatique des événements de transferts horizontaux entre espèces de drosophiles et lien avec la régulation des éléments transposables
- MLE-induced Likelihood for Markov Random Fields
- Joint Nonparametric Precision Matrix Estimation with Confounding
- 2 . 2 Approximating Marginal Likelihood of an MRF
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