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Author:

Qian, F. (Qian, F..) | Chen, R. (Chen, R..) | Wang, L. (Wang, L..)

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Scopus

Abstract:

In the case of multicollinearity, biased estimators are always introduced to correct the least squares estimator. In this paper, we propose a new biased estimator for the restricted linear model. The properties of the new estimator and its superiority over the restricted least squares estimator in terms of the mean square error and Pitman closeness criterion are theoretically analysed. Furthermore, we optimize and verify the feasibility of the new estimator using a numerical simulation. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Keyword:

Restricted least squares Restricted generalized ridge shrinkage estimator Pitman closeness criterion Mean square error criterion Multicollinearity

Author Community:

  • [ 1 ] [Qian F.]School of Science, Changzhou Institute of Technology, Changzhou, China
  • [ 2 ] [Chen R.]Faculty of Science, Beijing University of Technology, Beijing, China
  • [ 3 ] [Wang L.]Public Foundational courses Department, Nanjing Vocational University of Industry Technology, Nanjing, 210023, China

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Source :

Computational Statistics

ISSN: 0943-4062

Year: 2023

Issue: 3

Volume: 39

Page: 1403-1416

1 . 3 0 0

JCR@2022

ESI HC Threshold:9

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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