Confidence Sets Based on Sparse Estimators Are Necessarily Large
AbstractConfidence sets based on sparse estimators are shown to be large compared to more standard confidence sets, demonstrating that sparsity of an estimator comes at a substantial price in terms of the quality of the estimator. The results are set in a general parametric or semiparametric framework.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 5677.
Date of creation: Aug 2007
Date of revision:
sparse estimator; consistent model selection; post-model-selection estimator; penalized maximum likelihood; confidence set; coverage probability;
Find related papers by JEL classification:
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
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