Confidence Sets Based on Sparse Estimators Are Necessarily Large

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.

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Year of publication:	2007-08
Authors:	Pötscher, Benedikt M.
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	sparse estimator \| consistent model selection \| post-model-selection estimator \| penalized maximum likelihood \| confidence set \| coverage probability

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C44 - Statistical Decision Theory; Operations Research ; C1 - Econometric and Statistical Methods: General
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005014743