On the hurdle negative binomial regression model with excess zeros for a right truncated count data

On the hurdle negative binomial regression model with excess zeros for a right truncated count data

A Poisson regression model is well-known for modeling the data with response variable in form of counts. However, one often encounters the situation with excess zeros occurred in the observed responses. Therefore, Poisson model is not suitable any more for this kind of data. Thus, we propose to use...

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Main Authors: Saffari, Seyed Ehsan, Xu, Xiaojian, Adnan, Robiah, Fard, Adeleh Hashemi
Format: Article
Published: 2013
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Q Science
Online Access:http://eprints.utm.my/id/eprint/40947/
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.409472017-08-22T07:49:34Z http://eprints.utm.my/id/eprint/40947/ On the hurdle negative binomial regression model with excess zeros for a right truncated count data Saffari, Seyed Ehsan Xu, Xiaojian Adnan, Robiah Fard, Adeleh Hashemi Q Science A Poisson regression model is well-known for modeling the data with response variable in form of counts. However, one often encounters the situation with excess zeros occurred in the observed responses. Therefore, Poisson model is not suitable any more for this kind of data. Thus, we propose to use a hurdle negative binomial model. Furthermore, the response variable in such cases is truncated for some values. So, a truncated hurdle negative binomial model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimates using the maximum likelihood method are discussed and the goodness-of-fit for the regression model is examined. We study the effects of right truncation in terms of parameters estimation and their standard errors via an example and a simulation. 2013 Article PeerReviewed Saffari, Seyed Ehsan and Xu, Xiaojian and Adnan, Robiah and Fard, Adeleh Hashemi (2013) On the hurdle negative binomial regression model with excess zeros for a right truncated count data. Journal of Mathematical Research and Applications, 1 (1). pp. 1-9. ISSN 2095-2651
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science
spellingShingle Q Science
Saffari, Seyed Ehsan
Xu, Xiaojian
Adnan, Robiah
Fard, Adeleh Hashemi
On the hurdle negative binomial regression model with excess zeros for a right truncated count data
description A Poisson regression model is well-known for modeling the data with response variable in form of counts. However, one often encounters the situation with excess zeros occurred in the observed responses. Therefore, Poisson model is not suitable any more for this kind of data. Thus, we propose to use a hurdle negative binomial model. Furthermore, the response variable in such cases is truncated for some values. So, a truncated hurdle negative binomial model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimates using the maximum likelihood method are discussed and the goodness-of-fit for the regression model is examined. We study the effects of right truncation in terms of parameters estimation and their standard errors via an example and a simulation.
format Article
author Saffari, Seyed Ehsan
Xu, Xiaojian
Adnan, Robiah
Fard, Adeleh Hashemi
author_facet Saffari, Seyed Ehsan
Xu, Xiaojian
Adnan, Robiah
Fard, Adeleh Hashemi
author_sort Saffari, Seyed Ehsan
title On the hurdle negative binomial regression model with excess zeros for a right truncated count data
title_short On the hurdle negative binomial regression model with excess zeros for a right truncated count data
title_full On the hurdle negative binomial regression model with excess zeros for a right truncated count data
title_fullStr On the hurdle negative binomial regression model with excess zeros for a right truncated count data
title_full_unstemmed On the hurdle negative binomial regression model with excess zeros for a right truncated count data
title_sort on the hurdle negative binomial regression model with excess zeros for a right truncated count data
publishDate 2013
url http://eprints.utm.my/id/eprint/40947/
_version_ 1643650602336518144

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