GGM Knockoff Filter: False Discovery Rate Control for Gaussian Graphical Models

DOI10.1111/rssb.12430OpenAlexW3182969529MaRDI QIDQ5088254

Jinzhou Li, Marloes H. Maathuis

Publication date: 11 July 2022

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.11611

zbMATH Keywords

structure learningfalse discovery rate (FDR)Gaussian graphical model (GGM)knockoff frameworksample splitting and recycling

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (6)

Null-free false discovery rate control using decoy permutations ⋮ Time series graphical Lasso and sparse VAR estimation ⋮ Structure learning of exponential family graphical model with false discovery rate control ⋮ StarTrek: combinatorial variable selection with false discovery rate control ⋮ Reproducible learning in large-scale graphical models ⋮ Revisiting feature selection for linear models with FDR and power guarantees

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