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
Open accessAbstract
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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Cites
Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
Lambert, D. (1992) · Technometrics · doi:10.2307/1269547 · Cited by 3,988
Specification and testing of some modified count data models
Mullahy, J. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90002-3 · Cited by 1,870
Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
Hall, D. B. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.01030.x · Cited by 913
Inglis, J., Cox, D. R., & Hinkley, D. V. (1975) · Technometrics · doi:10.2307/1268442 · Cited by 685
Overdispersion: Models and estimation
Hinde, J., & Demétrio, C. G. B. (1998) · Computational Statistics & Data Analysis · doi:10.1016/s0167-9473(98)00007-3 · Cited by 598
Generalized poisson regression model
Consul, P. C., & Famoye, F. (1992) · Communications in Statistics - Theory and Methods · doi:10.1080/03610929208830766 · Cited by 388
Self-citationBöhning, D., Dietz, E., Schlattmann, P., Mendonça, L., & Kirchner, U. (1999) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/1467-985x.00130 · Cited by 377
Zero‐Altered and other Regression Models for Count Data with Added Zeros
Heilbron, D. C. (1994) · Biometrical Journal · doi:10.1002/bimj.4710360505 · Cited by 375
Models for count data with many zeros
Ridout, M. S., Demétrio, C. G. B., & Hinde, J. (1998) · Cited by 368
An Economic Analysis of Domestic Violence
Farmer, A., & Tiefenthaler, J. (1997) · Review of Social Economy · doi:10.1080/00346769700000004 · Cited by 364
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
- diamond
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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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