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K 1 K 2–Inflated Conway–Maxwell–Poisson Model: Bayesian Predictive Modeling with an Application in Soccer Matches

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Abstract

The purpose of this paper is two folds. First, to introduce a multiple inflated version of the Conway–Maxwell–Poisson model, that can be used flexibly to model count data when some values have high frequency along with over– or under–dispersion. Also, this model includes Poisson, Conway–Maxwell–Poisson (COMP), zero–inflated Poisson (ZIP), multiple–inflated Poisson, and zero–inflated Conway–Maxwell–Poisson (ZICOMP). Second, to estimate the future distribution from the multiple inflated Conway–Maxwell–Poisson model under the Kullback Leibler difference (loss) function. This model is fitted to the number of penalties scored in the Premier League’s 2019–20 season and its future distribution using Bayes and plug–in methods is estimated.
Original languageEnglish
Pages (from-to)295-304
Number of pages10
JournalAmerican Journal of Mathematical and Management Sciences
Volume41
Issue number4
DOIs
StatePublished - Jan 1 2022

Keywords

  • Bayes predictive distribution estimation
  • Kullback Leibler difference
  • Pearson Chi–squared test
  • Soccer match
  • count data
  • –inflated Conway–Maxwell–Poisson

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