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L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model

L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model In this paper, the L 1-norm estimators and the random weighted statistic for a semiparametric regression model are constructed, the strong convergence rates of estimators are obtain under certain conditions, the strong efficiency of the random weighting method is shown. A simulation study is conducted to compare the L 1-norm estimator with the least square estimator in term of approximate accuracy, and simulation results are given for comparison between the random weighting method and normal approximation method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mathematicae Applicatae Sinica Springer Journals

L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model

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L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model

Xue, Liu-gen; Zhu, Li-xing
Acta Mathematicae Applicatae Sinica , Volume 21 (2) – Jan 1, 2005

Abstract

In this paper, the L
1-norm estimators and the random weighted statistic for a semiparametric regression model are constructed, the strong convergence rates of estimators are obtain under certain conditions, the strong efficiency of the random weighting method is shown. A simulation study is conducted to compare the L
1-norm estimator with the least square estimator in term of approximate accuracy, and simulation results are given for comparison between the random weighting method and normal approximation method.

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References (8)

Publisher
Springer Journals
Copyright
Copyright © 2005 by Springer-Verlag Berlin Heidelberg
Subject
Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
ISSN
0168-9673
eISSN
1618-3932
DOI
10.1007/s10255-005-0237-8
Publisher site
See Article on Publisher Site

Abstract

In this paper, the L 1-norm estimators and the random weighted statistic for a semiparametric regression model are constructed, the strong convergence rates of estimators are obtain under certain conditions, the strong efficiency of the random weighting method is shown. A simulation study is conducted to compare the L 1-norm estimator with the least square estimator in term of approximate accuracy, and simulation results are given for comparison between the random weighting method and normal approximation method.

Journal

Acta Mathematicae Applicatae Sinica – Springer Journals

Published: Jan 1, 2005

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