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Comment on "A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models" by Chengguang Dai, Buyu Lin, Xin Xing, and Jun S. Liu.
- Source :
- Journal of the American Statistical Association; Sep2023, Vol. 118 Issue 543, p1566-1568, 3p
- Publication Year :
- 2023
-
Abstract
- In the present article, Dai et al. ([5]) studies FDR control of the GM and DS methods for generalized linear models (GLMs) under a unified framework. Specifically, Xing, Zhao, and Liu ([16]) develops the Gaussian Mirror (GM) method for controlling FDR in high-dimensional linear regressions. Wang and Ramdas ([15]) uses e-value and develops the e-BH procedure to control FDR. With the maturity of data collection techniques, the analysis of data with high-dimensional input is now routinely conducted. [Extracted from the article]
- Subjects :
- FALSE discovery rate
MATHEMATICAL statistics
STATISTICS
RANKING (Statistics)
Subjects
Details
- Language :
- English
- ISSN :
- 01621459
- Volume :
- 118
- Issue :
- 543
- Database :
- Complementary Index
- Journal :
- Journal of the American Statistical Association
- Publication Type :
- Academic Journal
- Accession number :
- 172404634
- Full Text :
- https://doi.org/10.1080/01621459.2023.2223689