Controlling the false discovery rate for latent factors via unit-rank deflation

DOI10.1016/j.spl.2021.109178zbMath1473.62203OpenAlexW3166817949MaRDI QIDQ2244589

Ruipeng Dong, Jia Zhou, Zemin Zheng

Publication date: 12 November 2021

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2021.109178

zbMATH Keywords

variable selectiondivide and conquerlatent factorFDR controlintegrative learning

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07)

Uses Software

• SOFAR

Cites Work

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• Statistics for high-dimensional data. Methods, theory and applications.
• Optimal selection of reduced rank estimators of high-dimensional matrices
• Controlling the false discovery rate via knockoffs
• RANK: Large-Scale Inference With Graphical Nonlinear Knockoffs
• Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
• SOFAR: Large-Scale Association Network Learning

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