Results 11 to 20 of about 120 (106)
Kibria–Lukman estimator for the Conway–Maxwell Poisson regression model: Simulation and applications
Scientific African, 2023 The Conway–Maxwell Poisson (COMP) regression model is one of the count data models to account for over– and under–dispersion. In regression analysis, when the explanatory variables are correlated, when there is multicollinearity problem, this inflates ...
Mohamed R. Abonazel +2 more
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A Family of Finite Mixture Distributions for Modelling Dispersion in Count Data
Stats, 2023 This paper considers the construction of a family of discrete distributions with the flexibility to cater for under-, equi- and over-dispersion in count data using a finite mixture model based on standard distributions. We are motivated to introduce this
Seng Huat Ong +3 more
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Mathematical and Computational Applications, 2023 Regression models in which the response variable has a compound distribution have applications in actuarial science. For example, the aggregate claim amount in a vehicle insurance portfolio can be modeled using a compound Poisson distribution.
Jahnavi Merupula +2 more
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A Flexible Multivariate Distribution for Correlated Count Data
Stats, 2021 Multivariate count data are often modeled via a multivariate Poisson distribution, but it contains an underlying, constraining assumption of data equi-dispersion (where its variance equals its mean).
Kimberly F. Sellers +3 more
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Enhanced Lot Acceptance Testing Based on Defect Counts and Posterior Odds Ratios
Axioms, 2022 Optimal defects-per-unit test plans based on posterior odds ratios are developed for the disposition of product lots. The number of nonconformities per unit is modeled by the Conway–Maxwell–Poisson distribution rather than the typical Poisson model.
Arturo J. Fernández
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Mathematics, 2023 Under-dispersed count data often appear in clinical trials, medical studies, demography, actuarial science, ecology, biology, industry and engineering.
Xun-Jian Li +4 more
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Frontiers in Applied Mathematics and Statistics, 2023 The Conway–Maxwell–Poisson (COMP) model is defined as a flexible count regression model used for over- and under-dispersion cases. In regression analysis, when the explanatory variables are highly correlated, this means that there is a multicollinearity ...
Mohamed R. Abonazel +4 more
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Dynamic Modeling of Spike Count Data With Conway-Maxwell Poisson Variability
Neural Computation, 2023 Abstract In many areas of the brain, neural spiking activity covaries with features of the external world, such as sensory stimuli or an animal's movement. Experimental findings suggest that the variability of neural activity changes over time and may provide information about the external world beyond the information provided by the ...
Ganchao Wei, Ian H. Stevenson
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The Use of the Conway–Maxwell–Poisson in the Seasonal Forecasting of Tropical Cyclones [PDF]
Weather and Forecasting, 2021 AbstractThe Conway–Maxwell–Poisson distribution improves the precision with which seasonal counts of tropical cyclones may be modeled. Conventionally the Poisson is used, which assumes that the formation and transit of tropical cyclones is the result of a Poisson process, such that their frequency distribution has equal mean and variance (“equi ...
Timothy D. Mitchell, Joanne Camp
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Conjugate analysis of the Conway-Maxwell-Poisson distribution
Bayesian Analysis, 2006 This article explores a Bayesian analysis of a generalization of the Poisson distribution. By choice of a second parameter v, both under-dispersed and over-dispersed data can be modeled. The Conway-Maxwell-Poisson distribution forms an exponential family of distributions, so it has sufficient statistics of fixed dimension as the sample size varies ...
Kadane, Joseph B. +4 more
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