A BAYESIAN ANALYSIS OF ENDOGENOUS SWITCHING MODELS FOR COUNT DATA
A BAYESIAN ANALYSIS OF ENDOGENOUS SWITCHING MODELS FOR COUNT DATA
复制标题
计数数据内源切换模型的贝叶斯分析
DOI：
10.14490/jjss.32.141
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
H. Kozumi
中科院分区：
文献类型：
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作者：
H. Kozumi
本文从贝叶斯的观点考虑了Terza（1998）提出的具有内生转换的计数模型。我们考虑马尔可夫链蒙特卡罗方法来估计模型的参数。此外，对非正态情形作了推广，并讨论了模型的确定。我们的方法与模拟和真实的数据集说明。
This paper considers the count model with endogenous switching proposed by Terza (1998) from a Bayesian point of view. We consider Markov chain Monte Carlo methods to estimate the parameters of the model. Furthermore, an extension is made to handle the case of non-normality and model determination is discussed. Our approach is illustrated with both simulated and real data sets.