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Cited by 266

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Zero-Inflated Generalized Poisson Regression Model with an Application to Domestic Violence Data

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Famoye, Felix, Singh, Karan P.·2021·Journal of Data Science

Abstract

The generalized Poisson regression model has been used to model dispersed count data. It is a good competitor to the negative binomial regression model when the count data is over-dispersed. Zero-inflated Poisson and zero-inflated negative binomial regression models have been proposed for the situations where the data generating process results into too many zeros. In this paper, we propose a zero-inflated generalized Poisson (ZIGP) regression model to model domestic violence data with too many zeros. Estimation of the model parameters using the method of maximum likelihood is provided. A score test is presented to test whether the number of zeros is too large for the generalized Poisson model to adequately fit the domestic violence data

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Metadata

Authors
Famoye, F., & Singh, K. P.
Venue
Journal of Data Science
Published
2021-07-13
Volume
4
Issue
1
Pages
117-130
ISSN
  • 1680-743X (ISSN-L)
  • 1683-8602
OpenAlex
W2183241504
Cited by
266
References
19
FWCI
14.63
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Zero-Inflated Generalized Poisson Regression Model with an Application to Domestic Violence Data. https://app.cochat.ai/papers/10.6339/jds.2006.04(1).257
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Famoye, F., & Singh, K. P. (2021). Zero-Inflated Generalized Poisson Regression Model with an Application to Domestic Violence Data. Journal of Data Science. https://doi.org/10.6339/jds.2006.04(1).257

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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