Inference in adaptive regression via the Kac-Rice formula

DOI10.1214/15-AOS1386zbMath1337.62304OpenAlexW233827914WikidataQ59756349 ScholiaQ59756349MaRDI QIDQ282472

Ryan J. Tibshirani, Joshua R. Loftus, Jonathan E. Taylor

Publication date: 12 May 2016

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aos/1458245734

zbMATH Keywords

Gaussian processesconvex analysisregularized regression

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Linear regression; mixed models (62J05)

Related Items

Inference in adaptive regression via the Kac-Rice formula, Powerful test based on conditional effects for genome-wide screening, Uniform asymptotic inference and the bootstrap after model selection, Scalable methods for Bayesian selective inference, Targeted Inference Involving High-Dimensional Data Using Nuisance Penalized Regression, Kac-Rice formulas and the number of solutions of parametrized systems of polynomial equations, Statistical proof? The problem of irreproducibility, Statistical learning and selective inference, A significance test for the lasso, Discussion: ``A significance test for the lasso, Rejoinder: ``A significance test for the lasso, A General Framework for Estimation and Inference From Clusters of Features, Selective inference via marginal screening for high dimensional classification, The volume-of-tube method for Gaussian random fields with inhomogeneous variance, Discussion: ``A significance test for the lasso, Discussion: ``A significance test for the lasso, Discussion: ``A significance test for the lasso, Discussion: ``A significance test for the lasso, Discussion: ``A significance test for the lasso

Uses Software

• softImpute
• covTest

Cites Work

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