A new estimator for the multicollinear Poisson regression model: simulation and application

The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicolline...

Descripción completa

Detalles Bibliográficos
Autores principales: Lukman, Adewale F., Adewuyi, Emmanuel, Månsson, Kristofer, Kibria, B. M. Golam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881247/
https://www.ncbi.nlm.nih.gov/pubmed/33580148
http://dx.doi.org/10.1038/s41598-021-82582-w
_version_ 1783650839192141824
author Lukman, Adewale F.
Adewuyi, Emmanuel
Månsson, Kristofer
Kibria, B. M. Golam
author_facet Lukman, Adewale F.
Adewuyi, Emmanuel
Månsson, Kristofer
Kibria, B. M. Golam
author_sort Lukman, Adewale F.
collection PubMed
description The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicollinearity problem. Some simulation experiments are conducted to compare the estimators' performance by using the mean squared error (MSE) criterion. For illustration purposes, aircraft damage data has been analyzed. The simulation results and the real-life application evidenced that the proposed estimator performs better than the rest of the estimators.
format Online
Article
Text
id pubmed-7881247
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-78812472021-02-16 A new estimator for the multicollinear Poisson regression model: simulation and application Lukman, Adewale F. Adewuyi, Emmanuel Månsson, Kristofer Kibria, B. M. Golam Sci Rep Article The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicollinearity problem. Some simulation experiments are conducted to compare the estimators' performance by using the mean squared error (MSE) criterion. For illustration purposes, aircraft damage data has been analyzed. The simulation results and the real-life application evidenced that the proposed estimator performs better than the rest of the estimators. Nature Publishing Group UK 2021-02-12 /pmc/articles/PMC7881247/ /pubmed/33580148 http://dx.doi.org/10.1038/s41598-021-82582-w Text en © The Author(s) 2021 Open Access This 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/.
spellingShingle Article
Lukman, Adewale F.
Adewuyi, Emmanuel
Månsson, Kristofer
Kibria, B. M. Golam
A new estimator for the multicollinear Poisson regression model: simulation and application
title A new estimator for the multicollinear Poisson regression model: simulation and application
title_full A new estimator for the multicollinear Poisson regression model: simulation and application
title_fullStr A new estimator for the multicollinear Poisson regression model: simulation and application
title_full_unstemmed A new estimator for the multicollinear Poisson regression model: simulation and application
title_short A new estimator for the multicollinear Poisson regression model: simulation and application
title_sort new estimator for the multicollinear poisson regression model: simulation and application
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881247/
https://www.ncbi.nlm.nih.gov/pubmed/33580148
http://dx.doi.org/10.1038/s41598-021-82582-w
work_keys_str_mv AT lukmanadewalef anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT adewuyiemmanuel anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT manssonkristofer anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT kibriabmgolam anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT lukmanadewalef newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT adewuyiemmanuel newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT manssonkristofer newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
AT kibriabmgolam newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication

Ejemplares similares