التفاصيل البيبلوغرافية
| العنوان: |
A flexible regression model for count data |
| المؤلفون: |
Sellers, Kimberly F., Shmueli, Galit |
| بيانات النشر: |
The Institute of Mathematical Statistics |
| سنة النشر: |
2010 |
| مصطلحات موضوعية: |
Conway–Maxwell-Poisson (COM-Poisson) distribution, dispersion, generalized linear models (GLM), generalized Poisson, stat |
| الوصف: |
Poisson regression is a popular tool for modeling count data and is applied in a vast array of applications from the social to the physical sciences and beyond. Real data, however, are often over- or under-dispersed and, thus, not conducive to Poisson regression. We propose a regression model based on the Conway–Maxwell-Poisson (COM-Poisson) distribution to address this problem. The COM-Poisson regression generalizes the well-known Poisson and logistic regression models, and is suitable for fitting count data with a wide range of dispersion levels. With a GLM approach that takes advantage of exponential family properties, we discuss model estimation, inference, diagnostics, and interpretation, and present a test for determining the need for a COM-Poisson regression over a standard Poisson regression. We compare the COM-Poisson to several alternatives and illustrate its advantages and usefulness using three data sets with varying dispersion. |
| نوع الوثيقة: |
text |
| اللغة: |
English |
| العلاقة: |
http://projecteuclid.org/euclid.aoas/1280842147Test |
| الإتاحة: |
http://projecteuclid.org/euclid.aoas/1280842147Test |
| حقوق: |
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| رقم الانضمام: |
edsbas.89DD38A2 |
| قاعدة البيانات: |
BASE |
