Large-Scale Inference of Multivariate Regression for Heavy-Tailed and Asymmetric Data
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Publication:6092949
DOI10.5705/ss.202021.0003OpenAlexW4200449544MaRDI QIDQ6092949
Wen Zhou, Unnamed Author, Wen-Xin Zhou
Publication date: 23 November 2023
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202021.0003
multivariate regressionlarge-scale multiple testingquantitative linguisticsgeneral linear hypothesesHuber lossheavy-tailed and/or skewed regression errors
Cites Work
- Unnamed Item
- Optimal rates of convergence for covariance matrix estimation
- Robust regression: Asymptotics, conjectures and Monte Carlo
- Challenging the empirical mean and empirical variance: a deviation study
- Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries
- Distributed statistical estimation and rates of convergence in normal approximation
- User-friendly covariance estimation for heavy-tailed distributions
- Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors
- Adaptive FDR control under independence and dependence
- A Factor Model Approach to Multiple Testing Under Dependence
- Adaptive Huber Regression
- Fully efficient robust estimation, outlier detection, and variable selection via penalized regression
- High-Dimensional Probability
- A Direct Approach to False Discovery Rates
- A New Principle for Tuning-Free Huber Regression
- Robust Estimation via Robust Gradient Estimation
- FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control
- Large-Scale Simultaneous Testing of Cross-Covariance Matrices with Applications to PheWAS
- Covariate-Assisted Ranking and Screening for Large-Scale Two-Sample Inference
- Statistical significance for genomewide studies
- Robust Estimation of a Location Parameter
- Error Distribution for Gene Expression Data
- Robust Statistics
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