Modified almost unbiased two-parameter estimator for the Poisson regression model with an application to accident data
(2021) In SORT 45(2). p.121-142- Abstract
Due to the large amount of accidents negatively affecting the wellbeing of the survivors and their families, a substantial amount of research is conducted to determine the causes of road accidents. This type of data come in the form of non-negative integers and may be modelled using the Poisson regression model. Unfortunately, the commonly used maximum likelihood estimator is unstable when the explanatory variables of the Poisson regression model are highly correlated. Therefore, this paper proposes a new almost unbiased estimator which reduces the instability of the maximum likelihood estimator and at the same time produce smaller mean squared error. We study the statistical properties of the proposed estimator and a simulation study... (More)
Due to the large amount of accidents negatively affecting the wellbeing of the survivors and their families, a substantial amount of research is conducted to determine the causes of road accidents. This type of data come in the form of non-negative integers and may be modelled using the Poisson regression model. Unfortunately, the commonly used maximum likelihood estimator is unstable when the explanatory variables of the Poisson regression model are highly correlated. Therefore, this paper proposes a new almost unbiased estimator which reduces the instability of the maximum likelihood estimator and at the same time produce smaller mean squared error. We study the statistical properties of the proposed estimator and a simulation study has been conducted to compare the performance of the estimators in the smaller mean squared error sense. Finally, Swedish traffic fatality data are analyzed to show the benefit of the proposed method.
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- author
- Alheety, Mustafa I. ; Qasim, Muhammad LU ; Månsson, Kristofer and Kibria, B. M.Golam
- publishing date
- 2021-07-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Applied traffic modeling, Maximum likelihood estimator, Mean squared error matrix, Poisson regression, Simulation study, Traffic fatality
- in
- SORT
- volume
- 45
- issue
- 2
- pages
- 22 pages
- publisher
- Institut d'Estadistica de Catalunya
- external identifiers
-
- scopus:85122852453
- ISSN
- 1696-2281
- DOI
- 10.2436/20.8080.02.112
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2021 Institut d'Estadistica de Catalunya. All rights reserved.
- id
- c06b8cf2-2a3d-4a64-9d07-da76ff90be6e
- date added to LUP
- 2025-04-01 09:30:41
- date last changed
- 2025-04-04 13:58:43
@article{c06b8cf2-2a3d-4a64-9d07-da76ff90be6e,
abstract = {{<p>Due to the large amount of accidents negatively affecting the wellbeing of the survivors and their families, a substantial amount of research is conducted to determine the causes of road accidents. This type of data come in the form of non-negative integers and may be modelled using the Poisson regression model. Unfortunately, the commonly used maximum likelihood estimator is unstable when the explanatory variables of the Poisson regression model are highly correlated. Therefore, this paper proposes a new almost unbiased estimator which reduces the instability of the maximum likelihood estimator and at the same time produce smaller mean squared error. We study the statistical properties of the proposed estimator and a simulation study has been conducted to compare the performance of the estimators in the smaller mean squared error sense. Finally, Swedish traffic fatality data are analyzed to show the benefit of the proposed method.</p>}},
author = {{Alheety, Mustafa I. and Qasim, Muhammad and Månsson, Kristofer and Kibria, B. M.Golam}},
issn = {{1696-2281}},
keywords = {{Applied traffic modeling; Maximum likelihood estimator; Mean squared error matrix; Poisson regression; Simulation study; Traffic fatality}},
language = {{eng}},
month = {{07}},
number = {{2}},
pages = {{121--142}},
publisher = {{Institut d'Estadistica de Catalunya}},
series = {{SORT}},
title = {{Modified almost unbiased two-parameter estimator for the Poisson regression model with an application to accident data}},
url = {{http://dx.doi.org/10.2436/20.8080.02.112}},
doi = {{10.2436/20.8080.02.112}},
volume = {{45}},
year = {{2021}},
}