2011
DOI: 10.1111/j.1539-6924.2011.01659.x
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Characterizing the Performance of the Conway‐Maxwell Poisson Generalized Linear Model

Abstract: Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model bas… Show more

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Cited by 53 publications
(39 citation statements)
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“…§ Third, despite its popularity in the literature [20,22,23], on the basis of the AIC the ZT CMP model is somewhat outperformed by the ZT Consul's generalized Poisson model in our case. Although the Consul's generalized Poisson distribution is not in the exponential family (and has no natural sufficient statistic), it is still a reasonable and competitive alternative to the CMP distribution according to our analysis.…”
Section: Discussionmentioning
confidence: 78%
“…§ Third, despite its popularity in the literature [20,22,23], on the basis of the AIC the ZT CMP model is somewhat outperformed by the ZT Consul's generalized Poisson model in our case. Although the Consul's generalized Poisson distribution is not in the exponential family (and has no natural sufficient statistic), it is still a reasonable and competitive alternative to the CMP distribution according to our analysis.…”
Section: Discussionmentioning
confidence: 78%
“…The following paragraph summarizes the simulation procedure for experiment one. The simulation setting considered in this study was first proposed by Francis et al (2012). The values of dispersion parameter are selected according to the finding in Table 1.…”
Section: Experiments Onementioning
confidence: 99%
“…The bias of an estimator is defined as the difference between an estimator's expected value and the true value of the parameter being estimated (Francis et al, 2012). The estimation bias of the dispersion parameter α is calculated as follows:…”
Section: Estimation Biasmentioning
confidence: 99%
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“…However, Francis et al (2012) Based on the new parameterization, Guikema and Coffelt (2008) developed a COMPoisson GLM framework to model discrete count data using Bayesian framework in WinBUGS (Spiegelhalter et al, 2003). Their modeling framework is a dual-link GLM in which both the mean and variance depend on the covariates.…”
Section: Conway-maxwell-poisson Modelmentioning
confidence: 99%