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

Abstract 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 mul...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Adewale F. Lukman, Emmanuel Adewuyi, Kristofer Månsson, B. M. Golam Kibria
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/58340e7ad13e44fa92450363b9cfc469
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:58340e7ad13e44fa92450363b9cfc469
record_format	dspace
spelling	oai:doaj.org-article:58340e7ad13e44fa92450363b9cfc4692021-12-02T14:27:02ZA new estimator for the multicollinear Poisson regression model: simulation and application10.1038/s41598-021-82582-w2045-2322https://doaj.org/article/58340e7ad13e44fa92450363b9cfc4692021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82582-whttps://doaj.org/toc/2045-2322Abstract 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.Adewale F. LukmanEmmanuel AdewuyiKristofer MånssonB. M. Golam KibriaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Adewale F. Lukman Emmanuel Adewuyi Kristofer Månsson B. M. Golam Kibria A new estimator for the multicollinear Poisson regression model: simulation and application
description	Abstract 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	article
author	Adewale F. Lukman Emmanuel Adewuyi Kristofer Månsson B. M. Golam Kibria
author_facet	Adewale F. Lukman Emmanuel Adewuyi Kristofer Månsson B. M. Golam Kibria
author_sort	Adewale F. Lukman
title	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_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_sort	new estimator for the multicollinear poisson regression model: simulation and application
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/58340e7ad13e44fa92450363b9cfc469
work_keys_str_mv	AT adewaleflukman anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT emmanueladewuyi anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT kristofermansson anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT bmgolamkibria anewestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT adewaleflukman newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT emmanueladewuyi newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT kristofermansson newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication AT bmgolamkibria newestimatorforthemulticollinearpoissonregressionmodelsimulationandapplication
_version_	1718391310400880640

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

Ejemplares similares