Censored generalized Poisson regression model

Felix Famoye, Weiren Wang

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper develops a censored generalized Poisson regression model that can be used to predict a response variable that is affected by one or more explanatory variables. The censored generalized Poisson regression model is suitable for modeling count data that exhibit either over- or under-dispersion. The regression parameters are estimated by the method of maximum likelihood and approximate tests for the adequacy of the model are discussed. Effect of censoring on the estimated biases and standard errors of the parameters is studied through simulation. Censored generalized Poisson regression model is applied to an observed data set.

Original languageEnglish
Pages (from-to)547-560
Number of pages14
JournalComputational Statistics and Data Analysis
Volume46
Issue number3
DOIs
StatePublished - Jun 15 2004

Keywords

  • Censored regression model
  • Deviance statistic
  • Dispersion parameter
  • Likelihood ratio statistic

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