Approximating the Conway-Maxwell-Poisson normalizing constant
Author(s) -
Burçin Şimşek,
Satish Iyengar
Publication year - 2016
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1604953s
Subject(s) - mathematics , approximation error , poisson distribution , approximations of π , constant (computer programming) , minimax approximation algorithm , integer (computer science) , mathematical analysis , statistics , computer science , programming language
The Conway-Maxwell-Poisson is a two-parameter family of distributions on the nonnegative integers. Its parameters and model the intensity and the dispersion, respectively. Its normalizing constant is not always easy to compute, so good approximations are needed along with an assessment of their error. Shmueli, et al. [12] derived an approximation assuming that is an integer, and gave an estimate of the relative error. Their numerical work showed that their approximation performs well in some parameter ranges but not in others. Our aims are to show that this approximation applies to all real > 0; to provide correction terms to this approximation; and to give different approximations for very small and very large. We then investigate the error terms numerically to assess our approximations. In parameter ranges for which Shmueli's approximation does poorly we show that our correction terms or alternative approximations give considerable improvement.
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