用贝叶斯分析方法检测两相拉普拉斯模型的变点

A. Jafari, M. Yarmohammadi, A. Rasekhi
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引用次数: 4

摘要

变点问题的一般形式是根据有序的观测序列确定未知位置,这样,两组观测并遵循不同的模型。本文研究了两相拉普拉斯模型的变点检测问题。我们的目标是找到随机变量模型参数发生变化的位置。采用贝叶斯方法对参数进行估计。然后通过仿真研究,讨论该方法的实现。对于模型的参数估计和变化点检测过程,使用了R语言中的R2OpenBUGS包。最后,提出了几个实证应用来说明这些方法的有效性。
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Bayesian analysis to detect change-point in two-phase Laplace model
The general form of the change-point problem is to determine the unknown location , based on an ordered sequence of observations such that, the two groups of observation and follow distinct models. In this paper the problem of changepoint detection of two-phase Laplace model is considered. Our object is to find the location of random variables where the parameters of their model are changed. The Bayesian method is used to estimate the parameters. Then by simulation studies, the implementation of proposed method will be discussed. For estimate the parameters of the model, and the procedure of the change-point detection the R2OpenBUGS Package in R is used. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures.
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来源期刊
Scientific Research and Essays
Scientific Research and Essays 综合性期刊-综合性期刊
自引率
0.00%
发文量
6
审稿时长
3.3 months
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