A new regression model for Poisson Lindley distribution with application

Abdul Hadi N. Ebraheim, Salah M. Mohamed, Khadeejah Abdullah Muayw

Abstract


The main goal of this study is to propose a new regression model using re-parameterization of the Poisson-Lindley distribution for seven parameters. The utility of real-world data is used to assess the accuracy of estimating algorithms. The suggested model is compared to well-known regression models for count data modelling, such as Poisson, on a real data set to demonstrate its utility. While fitting two real data sets, the (GPL7) linear model will be compared to the Poisson for seven parameters and the (GPL4) linear model will be compared to the Poisson for four parameters. The GPL7 linear model was found to be capable of fitting over-dispersed count data and to have the maximum log-likelihood, according to the results.

Full Text: PDF

Published: 2022-08-08

How to Cite this Article:

Abdul Hadi N. Ebraheim, Salah M. Mohamed, Khadeejah Abdullah Muayw, A new regression model for Poisson Lindley distribution with application, Commun. Math. Biol. Neurosci., 2022 (2022), Article ID 74

Copyright © 2022 Abdul Hadi N. Ebraheim, Salah M. Mohamed, Khadeejah Abdullah Muayw. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Commun. Math. Biol. Neurosci.

ISSN 2052-2541

Editorial Office: office@scik.org

 

Copyright ©2024 CMBN