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2003•Journal of the Korean Data and Information Science SocietyRequires access

An application to Multivariate Zero-Inflated Poisson Regression Model

Kyung Moo Kim

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Abstract

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correalated reponse variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE`s. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.

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What this paper is about

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correalated reponse variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE`s. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.

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Available abstract

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correalated reponse variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE`s. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.

Key concepts: Multivariate statistics, Poisson regression, Zero-inflated model, Bayesian multivariate linear regression, Statistics, Mathematics, Factor regression model, Univariate

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