Approximating the Conway-Maxwell-Poisson normalizing constant
نویسندگان
چکیده
منابع مشابه
Approximating the Conway–Maxwell–Poisson distribution normalization constant
By adding a second parameter, Conway and Maxwell created a new distribution for situations where data deviate from the standard Poisson distribution. This new distribution contains a normalization constant expressed as an infinite sum whose summation has no known closed-form expression. Shmueli et al. produced an approximation for this sum but proved only that it was valid for integer values of...
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The bivariate Poisson distribution is a popular distribution for modeling bivariate count data. Its basic assumptions and marginal equi-dispersion, however, may prove limiting in some contexts. To allow for data dispersion, we develop here a bivariate Conway–Maxwell–Poisson (COM–Poisson) distribution that includes the bivariate Poisson, bivariate Bernoulli, and bivariate geometric distributions...
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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 ris...
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This paper documents the performance of a Bayesian Conway-Maxwell-Poisson (COM-Poisson) generalized linear model (GLM). This distribution was originally developed as an extension of the Poisson distribution in 1962 and has a unique characteristic, in that it can handle both under-dispersed and over-dispersed count data. Previous work by the authors lead to the development of a dual-link GLM bas...
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ژورنال
عنوان ژورنال: Filomat
سال: 2016
ISSN: 0354-5180,2406-0933
DOI: 10.2298/fil1604953s