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20162026
most citedPanning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection

41 citations · 49 across the 7 of their papers we have counts for

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5 papers · 1 filter

stat.ME2025

Mosaic inference on panel data

Asher Spector, Rina Foygel Barber, Emmanuel Candès

Analysis of panel data via linear regression is widespread across disciplines. To perform statistical inference, such analyses typically assume that clusters of observations are jo…

stat.ME2024★ 2 cited

The mosaic permutation test: an exact and nonparametric goodness-of-fit test for factor models

Asher Spector, Rina Foygel Barber, Trevor Hastie +2

Financial firms often rely on fundamental factor models to explain correlations among asset returns and manage risk. Yet after major events, e.g., COVID-19, analysts may reassess w…

stat.ME2024★ 5 cited

Controlled Variable Selection from Summary Statistics Only? A Solution via GhostKnockoffs and Penalized Regression

Zhaomeng Chen, Zihuai He, Benjamin B. Chu +4

Identifying which variables do influence a response while controlling false positives pervades statistics and data science. In this paper, we consider a scenario in which we only h…

stat.ME2023★ 1 cited

Second-order group knockoffs with applications to GWAS

Benjamin B Chu, Jiaqi Gu, Zhaomeng Chen +4

Conditional testing via the knockoff framework allows one to identify -- among large number of possible explanatory variables -- those that carry unique information about an outcom…

stat.ME2016★ 41 cited

Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection

Emmanuel Candes, Yingying Fan, Lucas Janson +1

Many contemporary large-scale applications involve building interpretable models linking a large set of potential covariates to a response in a nonlinear fashion, such as when the…