Selective inference after likelihood- or test-based model selection in linear models

DOI10.1016/j.spl.2018.04.010zbMath1463.62205arXiv1706.09796OpenAlexW2759600886MaRDI QIDQ1644176

Sonja Greven, David Rügamer

Publication date: 21 June 2018

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

Full work available at URL: https://arxiv.org/abs/1706.09796

zbMATH Keywords

linear modelsAIClikelihood-based model selectionselective inferencetest-based model selection

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03)

Related Items (5)

Regularized projection score estimation of treatment effects in high-dimensional quantile regression ⋮ Optimal finite sample post-selection confidence distributions in generalized linear models ⋮ Approximate Selective Inference via Maximum Likelihood ⋮ Inference for \(L_2\)-boosting ⋮ Selective inference for additive and linear mixed models

Uses Software

• GitHub
• coinflibs

Cites Work

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• Exact post-selection inference, with application to the Lasso
• Valid post-selection inference
• Variable selection in infinite-dimensional problems
• Estimating the dimension of a model
• MODEL SELECTION AND INFERENCE: FACTS AND FICTION
• Note on a Conditional Property of Student's $t^1$

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