Applications of some discrete regression models for count data
نویسندگان
چکیده
منابع مشابه
Applications of some discrete regression models for count data
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 ...
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Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression mode...
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The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions ...
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In this paper, we propose Hurdle regression models for analysing count responses with extra zeros. A method of estimating maximum likelihood is used to estimate model parameters. The application of the proposed model is presented in insurance dataset. In this example, there are many numbers of claims equal to zero is considered that clarify the application of the model with a zero-inflat...
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ژورنال
عنوان ژورنال: Pakistan Journal of Statistics and Operation Research
سال: 2006
ISSN: 2220-5810,1816-2711
DOI: 10.18187/pjsor.v2i1.81