Parameter estimation on zero-inflated negative binomial regression with right truncated data

A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression mod...

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Main Authors: Seyed Ehsan Saffari, Robiah Adnan
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2012
Online Access:http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf
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recordtype eprints
spelling ukm-55862016-12-14T06:38:53Z http://journalarticle.ukm.my/5586/ Parameter estimation on zero-inflated negative binomial regression with right truncated data Seyed Ehsan Saffari, Robiah Adnan, A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodness-of-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated. Universiti Kebangsaan Malaysia 2012-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf Seyed Ehsan Saffari, and Robiah Adnan, (2012) Parameter estimation on zero-inflated negative binomial regression with right truncated data. Sains Malaysiana, 41 (11). pp. 1483-1487. ISSN 0126-6039 http://www.ukm.my/jsm/
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
language English
description A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodness-of-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated.
format Article
author Seyed Ehsan Saffari,
Robiah Adnan,
spellingShingle Seyed Ehsan Saffari,
Robiah Adnan,
Parameter estimation on zero-inflated negative binomial regression with right truncated data
author_facet Seyed Ehsan Saffari,
Robiah Adnan,
author_sort Seyed Ehsan Saffari,
title Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_short Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_full Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_fullStr Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_full_unstemmed Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_sort parameter estimation on zero-inflated negative binomial regression with right truncated data
publisher Universiti Kebangsaan Malaysia
publishDate 2012
url http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf
first_indexed 2023-09-18T19:44:34Z
last_indexed 2023-09-18T19:44:34Z
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