Detection of sparse positive dependence
From MaRDI portal
Publication:2293723
DOI10.1214/19-EJS1675zbMath1435.62224arXiv1811.07105OpenAlexW3003522222MaRDI QIDQ2293723
Ery Arias-Castro, Nicolas Verzelen, Rong Huang
Publication date: 5 February 2020
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1811.07105
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Related Items (4)
Testing equivalence of clustering ⋮ Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics ⋮ Signal-noise ratio of genetic associations and statistical power of SNP-set tests ⋮ Exact detection thresholds and minimax optimality of Chatterjee's correlation coefficient
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Innovated higher criticism for detecting sparse signals in correlated noise
- Higher criticism for large-scale inference, especially for rare and weak effects
- On the exact Berk-Jones statistics and their \(p\)-value calculation
- Measuring reproducibility of high-throughput experiments
- Some problems of hypothesis testing leading to infinitely divisible distributions
- Poisson approximation and the Chen-Stein method. With comments and a rejoinder by the authors
- Higher criticism for detecting sparse heterogeneous mixtures.
- Stein's method for concentration inequalities
- Distribution-free tests for sparse heterogeneous mixtures
- Optimal detection of weak positive latent dependence between two sequences of multiple tests
- Higher criticism thresholding: Optimal feature selection when useful features are rare and weak
- Optimal Detection of Sparse Mixtures Against a Given Null Distribution
- Optimal Detection of Heterogeneous and Heteroscedastic Mixtures
- Assessing replicability of findings across two studies of multiple features
- The sparse variance contamination model
- Testing Statistical Hypotheses
- A Combinatorial Central Limit Theorem
This page was built for publication: Detection of sparse positive dependence