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Title: The LASSO estimator: Distributional properties (English)
Author: Jagannath, Rakshith
Author: Upadhye, Neelesh S.
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 54
Issue: 4
Year: 2018
Pages: 778-797
Summary lang: English
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Category: math
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Summary: The least absolute shrinkage and selection operator (LASSO) is a popular technique for simultaneous estimation and model selection. There have been a lot of studies on the large sample asymptotic distributional properties of the LASSO estimator, but it is also well-known that the asymptotic results can give a wrong picture of the LASSO estimator's actual finite-sample behaviour. The finite sample distribution of the LASSO estimator has been previously studied for the special case of orthogonal models. The aim in this work is to generalize the finite sample distribution properties of LASSO estimator for a real and linear measurement model in Gaussian noise. In this work, we derive an expression for the finite sample characteristic function of the LASSO estimator, we then use the Fourier slice theorem to obtain an approximate expression for the marginal probability density functions of the one-dimensional components of a linear transformation of the LASSO estimator. (English)
Keyword: linear regression
Keyword: LASSO
Keyword: characteristic function
Keyword: finite sample probability distribution function
Keyword: Fourier-Slice theorem
Keyword: Cramer–Wold theorem
MSC: 60E05
MSC: 62E15
MSC: 62G05
MSC: 62J05
idZBL: Zbl 06987034
idMR: MR3863256
DOI: 10.14736/kyb-2018-4-0778
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Date available: 2018-10-30T14:51:44Z
Last updated: 2023-10-03
Stable URL: http://hdl.handle.net/10338.dmlcz/147424
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