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Zero-inflated models and estimation in zero-inflated Poisson distribution

机译:零膨胀模型和泊松分布的零估计

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In this paper, we briefly overview different zero-inflated probability distributions. We compare the performance of the estimates of Poisson, Generalized Poisson, ZIP, ZIGP and ZINB models through Mean square error (MSE), bias and Standard error (SE) when the samples are generated from ZIP distribution. We propose a new estimator referred to as probability estimator (PE) of inflation parameter of ZIP distribution based on moment estimator (ME) of the mean parameter and compare its performance with ME and maximum likelihood estimator (MLE) through a simulation study. We use the PE along with ME and MLE to fit ZIP distribution to various zero-inflated datasets and observe that the results do not differ significantly. We recommend using PE in place of MLE since it is easy to calculate and the simulation study in this paper demonstrates that the PE performs as good as MLE irrespective of the sample size.
机译:在本文中,我们简要概述了不同的零膨胀概率分布。当样本从ZIP分布生成时,我们通过均方误差(MSE),偏差和标准误差(SE)比较Poisson,广义Poisson,ZIP,ZIGP和ZINB模型的估计性能。我们基于平均参数的矩估计量(ME)提出了一种新的估计器,称为ZIP分布膨胀参数的概率估计器(PE),并通过仿真研究将其性能与ME和最大似然估计器(MLE)进行了比较。我们将PE与ME和MLE一起使用以使ZIP分布适合各种零膨胀数据集,并观察到结果没有显着差异。我们建议使用PE代替MLE,因为它易于计算,并且本文的仿真研究表明,无论样本大小如何,PE的性能都与MLE一样好。

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