Pötscher, Benedikt M. (2007): Confidence Sets Based on Sparse Estimators Are Necessarily Large.
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Abstract
Confidence 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.
Item Type:  MPRA Paper 

Original Title:  Confidence Sets Based on Sparse Estimators Are Necessarily Large 
Language:  English 
Keywords:  sparse estimator, consistent model selection, postmodelselection estimator, penalized maximum likelihood, confidence set, coverage probability 
Subjects:  C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C44  Operations Research; Statistical Decision Theory C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General 
Item ID:  5677 
Depositing User:  Benedikt Poetscher 
Date Deposited:  10. Nov 2007 02:43 
Last Modified:  19. Feb 2013 07:08 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/5677 
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