On the mixed Kibria–Lukman estimator for the linear regression model

This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria–Lukman estimator...

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Detalles Bibliográficos
Autores principales: Chen, Hongmei, Wu, Jibo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300599/
https://www.ncbi.nlm.nih.gov/pubmed/35859042
http://dx.doi.org/10.1038/s41598-022-16689-z
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author Chen, Hongmei
Wu, Jibo
author_facet Chen, Hongmei
Wu, Jibo
author_sort Chen, Hongmei
collection PubMed
description This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria–Lukman estimator as special cases. In addition, we discuss the advantages of the new estimator based on MSEM criterion, and illustrate the theoretical results through examples and simulation analysis.
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spelling pubmed-93005992022-07-22 On the mixed Kibria–Lukman estimator for the linear regression model Chen, Hongmei Wu, Jibo Sci Rep Article This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria–Lukman estimator as special cases. In addition, we discuss the advantages of the new estimator based on MSEM criterion, and illustrate the theoretical results through examples and simulation analysis. Nature Publishing Group UK 2022-07-20 /pmc/articles/PMC9300599/ /pubmed/35859042 http://dx.doi.org/10.1038/s41598-022-16689-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chen, Hongmei
Wu, Jibo
On the mixed Kibria–Lukman estimator for the linear regression model
title On the mixed Kibria–Lukman estimator for the linear regression model
title_full On the mixed Kibria–Lukman estimator for the linear regression model
title_fullStr On the mixed Kibria–Lukman estimator for the linear regression model
title_full_unstemmed On the mixed Kibria–Lukman estimator for the linear regression model
title_short On the mixed Kibria–Lukman estimator for the linear regression model
title_sort on the mixed kibria–lukman estimator for the linear regression model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300599/
https://www.ncbi.nlm.nih.gov/pubmed/35859042
http://dx.doi.org/10.1038/s41598-022-16689-z
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