Model Selection confidence sets by likelihood ratio testing

DOI10.5705/ss.202017.0006zbMath1427.62015arXiv1709.04342OpenAlexW2963468210MaRDI QIDQ5226611

Chao Zheng, Davide Ferrari, Yuhong Yang

Publication date: 1 August 2019

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1709.04342

zbMATH Keywords

likelihood ratio testadaptive samplingmodel selection confidence setoptimal detectability condition

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Parametric hypothesis testing (62F03) Hypothesis testing in multivariate analysis (62H15) Sampling theory, sample surveys (62D05)

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Discussion on Prior-based Bayesian Information Criterion (PBIC) by M. J. Bayarri, James O. Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi, and Ingmar Visser ⋮ Order selection with confidence for finite mixture models ⋮ Penalized estimating equations for generalized linear models with multiple imputation ⋮ Measures of Uncertainty for Shrinkage Model Selection ⋮ Simple measures of uncertainty for model selection ⋮ Confidence graphs for graphical model selection ⋮ Visualization and assessment of model selection uncertainty ⋮ Subdata selection algorithm for linear model discrimination

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