Post-model-selection inference in linear regression models: An integrated review-Reference-Cited by-同舟云学术

Post-model-selection inference in linear regression models: An integrated review

Published:2022-01-01 Issue:none Volume:16 Page:
ISSN:1935-7516
Container-title:Statistics Surveys
language:
Short-container-title:Statist. Surv.

Author:

Zhang Dongliang¹,Khalili Abbas²,Asgharian Masoud²

Affiliation:

1. Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA

2. Department of Mathematics and Statistics, McGill University, Montréal, QC, Canada

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference121 articles.

1. Azais, J., Castro, Y. D. & Mourareau, S. (2018), ‘Power of the spacing test for least-angle regression’, Bernoulli 24, 465–492.

2. Bachoc, F., Blanchard, G. & Neuvial, P. (2018), ‘On the post selection inference constant under restricted isometry properties’, Electronic Journal of Statistics 12, 3736–3757.

3. Bachoc, F., Leeb, H. & Pötscher, B. M. (2019), ‘Valid confidence intervals for post-model-selection predictors’, The Annals of Statistics 47, 1475–1504.

4. Bachoc, F., Preinerstorfer, D. & Steinberger, L. (2020), ‘Uniformly valid confidence intervals post-model-selection’, The Annals of Statistics 48, 440–463.

5. Bancroft, T. A. & Han, C.-P. (1977), ‘Inference based on conditional specification: a note and a bibliography’, International Statistical Review 45, 117–127.

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