Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity

Öznur İşçi Güneri; Burcu Durmuş

doi:10.53570/jnt.902066

EN

Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity

Abstract

The Poisson regression model is widely used for count data. This model assumes equidispersion. In practice, equidispersion is seldom reflected in data. However, in real-life data, the variance usually exceeds the mean. This situation is known as overdispersion. Negative binomial distribution and other Poisson mix models are often used to model overdispersion count data. Another extension of the negative binomial distribution in another model for count data is the univariate generalized Waring. In addition, the model developed by Famoye can be used in the analysis of count data. When the count data contains a large number of zeros, it is necessary to use zero-inflated models. In this study, different generalized regression models are emphasized for the analysis of excessive zeros count data. For this purpose, a real data set was analysed with the generalized Poisson model, generalized negative binomial model, generalized negative binomial Famoye, generalized Waring model, and the foregoing zero-inflated models. Log-likelihood, Akaike information criterion, Bayes information criterion, Vuong statistics were used for model comparisons.

Keywords

Count data, overdispersion, generalized distribution models, zero-inflated

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Details

Primary Language

English

Subjects

Applied Mathematics

Journal Section

Research Article

Authors

Öznur İşçi Güneri ^*
0000-0003-3677-7121
Türkiye

Burcu Durmuş
0000-0002-0298-0802
Türkiye

Publication Date

June 30, 2021

Submission Date

March 23, 2021

Acceptance Date

June 4, 2021

Published in Issue

Year 2021 Number: 35

DOI

https://doi.org/10.53570/jnt.902066

IZ

https://izlik.org/JA57LX55WH

APA

İşçi Güneri, Ö., & Durmuş, B. (2021). Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity. Journal of New Theory, 35, 48-61. https://doi.org/10.53570/jnt.902066

AMA

1.İşçi Güneri Ö, Durmuş B. Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity. JNT. 2021;(35):48-61. doi:10.53570/jnt.902066

Chicago

İşçi Güneri, Öznur, and Burcu Durmuş. 2021. “Models for Overdispersion Count Data With Generalized Distribution: An Application to Parasites Intensity”. Journal of New Theory, nos. 35: 48-61. https://doi.org/10.53570/jnt.902066.

EndNote

İşçi Güneri Ö, Durmuş B (June 1, 2021) Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity. Journal of New Theory 35 48–61.

IEEE

[1]Ö. İşçi Güneri and B. Durmuş, “Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity”, JNT, no. 35, pp. 48–61, June 2021, doi: 10.53570/jnt.902066.

ISNAD

İşçi Güneri, Öznur - Durmuş, Burcu. “Models for Overdispersion Count Data With Generalized Distribution: An Application to Parasites Intensity”. Journal of New Theory. 35 (June 1, 2021): 48-61. https://doi.org/10.53570/jnt.902066.

JAMA

1.İşçi Güneri Ö, Durmuş B. Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity. JNT. 2021;:48–61.

MLA

İşçi Güneri, Öznur, and Burcu Durmuş. “Models for Overdispersion Count Data With Generalized Distribution: An Application to Parasites Intensity”. Journal of New Theory, no. 35, June 2021, pp. 48-61, doi:10.53570/jnt.902066.

Vancouver

1.Öznur İşçi Güneri, Burcu Durmuş. Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity. JNT. 2021 Jun. 1;(35):48-61. doi:10.53570/jnt.902066

Modelling the Number of Pneumonia Cases among Toddlers in East Java Province with the Generalized Additive Model Approach

Jurnal Pijar MIPA

https://doi.org/10.29303/jpm.v21i3.11595

Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity

Abstract

Models for Overdispersion Count Data with Generalized Distribution: An Application to Parasites Intensity

Abstract

Keywords

References

Details

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Subjects

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Publication Date

Submission Date

Acceptance Date

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DOI

IZ

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