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Bayesian analysis to detect change-point in two-phase Laplace model

机译:贝叶斯分析在两相Laplace模型中检测变化点

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The general form of the change-point problem is to determine the unknown location m, based on an ordered sequence of observations X1,X2,.., Xm, Xm+1,..., Xn such that, the two groups of observation X1,X2,.., Xm and Xm+1,..., Xn follow distinct models. In this paper the problem of change-point 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.  
机译:变更点问题的一般形式是,根据观测值X1,X2,..,Xm,Xm + 1,...,Xn的有序序列来确定未知位置m。这样,两组观察X1,X2,..,Xm和Nm + 1,...,Xn遵循不同的模型。本文考虑了两相拉普拉斯模型的变化点检测问题。我们的目标是找到随机变量的位置,在这些位置上,其模型参数发生了变化。贝叶斯方法用于估计参数。然后通过仿真研究,将讨论所提出方法的实现。为了估计模型的参数以及更改点检测的过程,使用了R中的R2OpenBUGS软件包。最后,提出了一些经验应用来说明该程序的有效性。  

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