Poisson回归与Conway Maxwell Poisson模型的仿真比较

Sarah Adnan Radam, Lamyaa Mohammed Ali Hameed
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引用次数: 0

摘要

回归模型是现代研究中使用的最重要的模型之一,特别是研究和健康研究,因为它们取得了重要的结果。本研究采用泊松回归模型(Poisson regression Model)和Conway-Max Well- Poisson回归模型(Conway-Max - Well- Poisson)两种回归模型,在不同样本量(n = 25、50、100)和重复数(r = 1000)的情况下,采用模拟方法对两种模型进行比较,并从中选择最佳模型。采用Matlab程序进行了仿真实验,结果表明,对于相同的分布,均方误差准则(MSE)和Akaiki准则(AIC)均显示了泊松模型的优越性。论文类型:研究论文。
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Comparison of Poisson Regression and Conway Maxwell Poisson Models Using Simulation
Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution. Paper type: Research paper.  
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