In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The estimation and inferences of the model parameters were made considering a Bayesian approach using the algorithm of Hamiltonian Markov chain Monte Carlo methods to simulate samples of the joint posterior distribution of interest. Two applications were made for the analysis of paired count data.

中文翻译：

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哈密​​顿量MCMC的零修正Skellam模型的贝叶斯方法

本文介绍了零修正泊松差，并介绍了它们在成对计数数据分析中的可能应用。考虑到贝叶斯方法，使用哈密顿马尔可夫链蒙特卡罗方法算法对模型参数的估计和推论，以模拟感兴趣的联合后验分布。进行了两个应用程序来分析配对计数数据。