Beta
25927

Modified Poisson Regression Models of Count Data and Parameter Estimation

Article

Last updated: 22 Jan 2023

Subjects

-

Tags

-

Abstract

This paper discusses the use of regression models of count data. It presents the estimation of the parameters for Poisson regression and zero-truncated Poisson regression models using the maximum likelihood method. We are interested in studying the performance of the estimators of modified Poisson regression models of count data. An assessment of the maximum likelihood estimates of the parameters is presented through a numerical study for different sample sizes for each model. Two empirical applications for non-truncated and truncated count data are presented, the first studies the effect of wave damage to cargo-ship and the second application investigates the length of hospital stay in days.

DOI

10.21608/jsfc.2015.25927

Keywords

Count data models, Poisson regression, generalized linear models, zero-truncated Poisson

Authors

First Name

Eman

Last Name

M. Sewilam

MiddleName

-

Affiliation

Dr. Eman M. Sewilam Mona M. AbdeL-Zaher Faculty of Commerce, ALAzhar University, Girls' Branch, Cairo

Email

-

City

-

Orcid

-

Volume

14

Article Issue

2

Related Issue

4693

Issue Date

2015-07-01

Receive Date

2015-01-17

Publish Date

2015-07-01

Page Start

1

Page End

38

Print ISSN

1687-322X

Link

https://jsfc.journals.ekb.eg/article_25927.html

Detail API

https://jsfc.journals.ekb.eg/service?article_code=25927

Order

5

Type

المقالة الأصلية

Type Code

761

Publication Type

Journal

Publication Title

المجلة العلمية لقطاع کليات التجارة

Publication Link

https://jsfc.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023