A strong law of large numbers for simultaneously testing parameters of Lancaster bivariate distributions
From MaRDI portal
Publication:2216978
DOI10.1016/j.spl.2020.108911zbMath1455.62106arXiv2003.02805OpenAlexW3081002999MaRDI QIDQ2216978
Publication date: 18 December 2020
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2003.02805
strong law of large numbersorthogonal polynomialsfalse discovery proportionLancaster bivariate distributions
Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15) Strong limit theorems (60F15)
Related Items (1)
Cites Work
- Unnamed Item
- Asymptotic FDR control under weak dependence: a counterexample
- Strong laws of large numbers for weakly correlated random variables
- Lancaster bivariate probability distributions with Poisson, negative binomial and gamma margins
- A strong law of large numbers related to multiple testing normal means
- Uniformly consistently estimating the proportion of false null hypotheses via Lebesgue-Stieltjes integral equations
- Dependency and false discovery rate: asymptotics
- The asymptotic expansion of a ratio of gamma functions
- The effect of correlation in false discovery rate estimation
- Estimating False Discovery Proportion Under Arbitrary Covariance Dependence
- Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
- Variance of the Number of False Discoveries
- The Empirical Distribution of a Large Number of Correlated Normal Variables
- Some Results on the Control of the False Discovery Rate under Dependence
- The Canonical Correlation Coefficients of Bivariate Gamma Distributions
- On empirical distribution function of high-dimensional Gaussian vector components with an application to multiple testing
This page was built for publication: A strong law of large numbers for simultaneously testing parameters of Lancaster bivariate distributions
