Pötscher, Benedikt M. and Schneider, Ulrike (2007): On the distribution of the adaptive LASSO estimator.
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Abstract
We study the distribution of the adaptive LASSO estimator (Zou (2006)) in finite samples as well as in the large-sample limit. The large-sample distributions are derived both for the case where the adaptive LASSO estimator is tuned to perform conservative model selection as well as for the case where tuning results in consistent model selection. We show that the finite-sample as well as the large-sample distributions are typically highly non-normal, regardless of the choice of the tuning parameter. The uniform convergence rate is also obtained, and is shown to be slower than n^{-1/2} in case the estimator is tuned to perform consistent model selection. In particular, these results question the statistical relevance of the `oracle' property of the adaptive LASSO estimator established in Zou 2006). Moreover, we also provide an impossibility result regarding the estimation of the distribution function of the adaptive LASSO estimator.
Item Type: | MPRA Paper |
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Original Title: | On the distribution of the adaptive LASSO estimator |
Language: | English |
Keywords: | Penalized maximum likelihood, LASSO, adaptive LASSO, nonnegative garotte, finite-sample distribution, asymptotic distribution, oracle property, estimation of distribution, uniform consistency |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C20 - General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection |
Item ID: | 6913 |
Depositing User: | Benedikt Poetscher |
Date Deposited: | 30 Jan 2008 10:22 |
Last Modified: | 28 Sep 2019 11:23 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/6913 |
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