دورية أكاديمية

The COM‐Poisson model for count data: a survey of methods and applications

التفاصيل البيبلوغرافية
العنوان: The COM‐Poisson model for count data: a survey of methods and applications
المؤلفون: Sellers, Kimberly F., Borle, Sharad, Shmueli, Galit
المصدر: Applied Stochastic Models in Business and Industry ; volume 28, issue 2, page 104-116 ; ISSN 1524-1904 1526-4025
بيانات النشر: Wiley
سنة النشر: 2011
المجموعة: Wiley Online Library (Open Access Articles via Crossref)
الوصف: The Poisson distribution is a popular distribution for modeling count data, yet it is constrained by its equidispersion assumption, making it less than ideal for modeling real data that often exhibit over‐dispersion or under‐dispersion. The COM‐Poisson distribution is a two‐parameter generalization of the Poisson distribution that allows for a wide range of over‐dispersion and under‐dispersion. It not only generalizes the Poisson distribution but also contains the Bernoulli and geometric distributions as special cases. This distribution's flexibility and special properties have prompted a fast growth of methodological and applied research in various fields. This paper surveys the different COM‐Poisson models that have been published thus far and their applications in areas including marketing, transportation, and biology, among others. Copyright © 2011 John Wiley & Sons, Ltd.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1002/asmb.918
الإتاحة: https://doi.org/10.1002/asmb.918Test
حقوق: http://onlinelibrary.wiley.com/termsAndConditions#vorTest
رقم الانضمام: edsbas.5DFAC73F
قاعدة البيانات: BASE