首页> 外文期刊>Neural, Parallel & Scientific Computations >A BAYESIAN ANALYSIS OF MULTIPLE CHANGES IN THE VARIANCE OF FIRST- ORDER AUTOREGRESSIVE TIME SERIES MODELS.
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A BAYESIAN ANALYSIS OF MULTIPLE CHANGES IN THE VARIANCE OF FIRST- ORDER AUTOREGRESSIVE TIME SERIES MODELS.

机译:一阶自回归时间序列模型的方差多个变化的贝叶斯分析。

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摘要

The problem of a change in the mean of a sequence of random variables at an unknown time point has been addressed extensively in the literature. But, the problem of a change in the variance at an unknown time point has, however, been covered less widely. This paper analyses a sequence of first order autoregressive time series model in which me variance may have subjected to multiple changes at an unknown time points. Posterior distributions are found both for the unknown points of time at which the changes occurred and for the parameters of the model. A numerical example is illustrated.
机译:文献中已经广泛地解决了在未知时间点随机变量序列的均值变化的问题。但是,在未知时间点方差变化的问题却没有得到广泛涉及。本文分析了一阶自回归时间序列模型的序列,其中我方差可能在未知时间点经历了多次变化。发现了发生变化的未知时间点和模型参数的后验分布。举例说明了一个数值示例。

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