On the performance of principal component Liu-type estimator under the mean square error criterion
type: Item
instance of: scholarly article
title: On the performance of principal component Liu-type estimator under the mean square error criterion
zbMATH Open document ID: 1397.62256
DOI: 10.1155/2013/858794
author: Jibo Wu
published in: Journal of Applied Mathematics
publication date: 2018-10-10T00:00:00Z
review text: Summary: We [Research on the properties of parameter estimation in linear regression model. Chongqing, China: Chongqing University (PhD Thesis) (2013)] proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu estimator, Liu-type estimator, \(r\)-\(k\) class estimator, and \(r\)-\(d\) class estimator. In this paper, firstly we use a new method to propose the principal component Liu-type estimator; then we study the superior of the new estimator by using the scalar mean squares error criterion. Finally, we give a numerical example to show the theoretical results.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62J07
zbMATH DE Number: 6950911
Wikidata QID: Q59004924
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/858794
OpenAlex ID: W2138614078
DBLP publication ID: journals/jam/Wu13a
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description: scientific article; zbMATH DE number 6950911