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Bayesian Statistical Modeling: Comparisons Between Poisson and Its Zero-Inflated Regression Model

机译:贝叶斯统计建模:泊松与其零充气复回模型的比较

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In this paper, we fit Poisson regression model and its Zero-Inflated version in Bayesian framework, to Malaysian motor vehicle claim count data, in order to study the differences between the models. The models are tested to Third Party Property Damage coverage data which contains sizeable amount of zero claims. The posterior distributions for both models are produced using Markov Chain Monte Carlo (MCMC) simulation to estimate their parameters. The results show that the Bayesian Zero-Inflated Poisson model has superiority over the standard Bayesian Poisson model based on the Deviance Information Criterion (DIC) values.
机译:在本文中,我们将泊松回归模型及其在贝叶斯框架中的零充气版本,到马来西亚机动车索赔计数数据,以研究模型之间的差异。该模型测试到第三方财产损坏覆盖数据,该数据包含相当大的索赔。两种模型的后部分布是使用Markov链蒙特卡罗(MCMC)模拟生产的,以估计其参数。结果表明,贝叶斯零充气的泊松模型基于偏差信息标准(DIC)值对标准贝叶斯泊松模型具有优势。

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