The distribution of a linear predictor after model selection: conditional finite-sample distributions and asymptotic approximations

DOI10.1016/j.jspi.2004.04.005zbMath1066.62071OpenAlexW2065568197MaRDI QIDQ2485973

Hannes Leeb

Publication date: 5 August 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2004.04.005

zbMATH Keywords

Model selectionModel uncertaintyDistribution of post-model-selection estimatorsInference after model selectionLinear predictor constructed after model selectionPre-test estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Point estimation (62F10) Exact distribution theory in statistics (62E15)

Related Items (7)

On the impact of model selection on predictor identification and parameter inference ⋮ Conditional predictive inference post model selection ⋮ PREDICTION/ESTIMATION WITH SIMPLE LINEAR MODELS: IS IT REALLY THAT SIMPLE? ⋮ Can one estimate the conditional distribution of post-model-selection estimators? ⋮ Preliminary test and estimation in some multifactor diffusion processes ⋮ CAN ONE ESTIMATE THE UNCONDITIONAL DISTRIBUTION OF POST-MODEL-SELECTION ESTIMATORS? ⋮ Inference after variable selection using restricted permutation methods

Cites Work

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• Asymptotic properties of maximum likelihood estimators based on conditional specification
• The distribution of estimators after model selection:large and small sample results
• THE FINITE-SAMPLE DISTRIBUTION OF POST-MODEL-SELECTION ESTIMATORS AND UNIFORM VERSUS NONUNIFORM APPROXIMATIONS
• On the Large-Sample Minimal Coverage Probability of Confidence Intervals After Model Selection

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