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Applications of some discrete regression models for count data

Pakistan Journal of Statistics and Operation Research

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Title Applications of some discrete regression models for count data
 
Creator Kibria, B. M. Golam
 
Description In this paper we have considered several regression models to fit the count data that encounter in the field of Biometrical, Environmental, Social Sciences and Transportation Engineering. We have fitted Poisson (PO), Negative Binomial (NB), Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) regression models to run-off-road (ROR) crash data which collected on arterial roads in south region (rural) of Florida State. To compare the performance of these models, we analyzed data with moderate to high percentage of zero counts. Because the variances were almost three times greater than the means, it appeared that both NB and ZINB models performed better than PO and ZIP models for the zero inflated and over dispersed count data.
 
Publisher College of Statistical and Actuarial Sciences
 
Date 2006-01-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://www.pjsor.com/index.php/pjsor/article/view/81
10.18187/pjsor.v2i1.81
 
Source Pakistan Journal of Statistics and Operation Research; Vol 2. No. 1, Jan 2006; 1-16
2220-5810
1816-2711
 
Language eng
 
Relation http://www.pjsor.com/index.php/pjsor/article/view/81/58