A Bayesian analysis of zero-inflated generalized Poisson model
A Bayesian analysis of zero-inflated generalized Poisson model
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DOI：
10.1016/s0167-9473(02)00154-8
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发表时间：
2003-02-28
影响因子：
1.8
通讯作者：
Biswas, A
中科院分区：
文献类型：
--
作者：
Angers, JF;Biswas, A
在几个现实生活中的例子中，人们遇到了计数数据，其中零的数量使得通常的泊松分布不适合该数据。通常情况下，零的数量很大，因此数据是零膨胀的。在这种情况下，可以考虑零膨胀的广义泊松模型，并进行贝叶斯分析。讨论了一些合适的先验，并利用蒙特卡罗积分和重要抽样得到了后验。给出了未来观测的预测密度。这些技术是用一个真实的数据集来说明的。计算在很大程度上支持这一方法。(C)2002 Elsevier Science B.V.保留所有权利。
In several real-life examples one encounters count data where the number of zeros is such that the usual Poisson distribution does not fit the data. Quite often the number of zeros is large, and hence the data is zero inflated. In this situation, a zero-inflated generalized Poisson model can be considered and a Bayesian analysis can be carried out. Some appropriate priors are discussed and the posteriors are obtained using Monte-Carlo integration with importance sampling. The predictive density of the future observation is also obtained. The techniques are illustrated using a real-life data set. Computations largely support the methodology. (C) 2002 Elsevier Science B.V. All rights reserved.