正态分布下多个方差转变点的检测与方法探讨
A Method of Detecting Multiple Change Point for Normal Distribution Process
DOI: 10.12677/AAM.2016.53040, PDF,    科研立项经费支持
作者: 沈卉卉：湖北经济学院，湖北 武汉；中国地质大学，湖北 武汉
关键词: 转变点；贝叶斯方法；极大似然方法；先验分布；似然密度函数；Change Point； Bayesian Method； Maximum Likelihood Method； Prior Distribution； Likelihood Density Function
摘要: 经济系统数学模型中含有多个转变点的结构模型问题，本文对在均值相同情况下，方差多个转变点的检测方法采取的是将贝叶斯方法和极大似然方法结合起来，利用贝叶斯方法消去多余参数，极大似然方法可以回避转变点个数的先验分布信息未知的问题，给出有效的检测方法。
Abstract: The problem of structure model occurs multiple change points in the economic system of mathe-matical models. In this paper, we give the detection method for change point problems about the variance changes. We combine the Bayesian method with the maximum likelihood method on the detection about the variance multiple change points in the same mean. The elimination extra pa-rameters can make use of Bayesian method; the maximum likelihood method can avoid the un-known problems of the prior distribution information of the change points number. It is a practical method.
文章引用：沈卉卉. 正态分布下多个方差转变点的检测与方法探讨[J]. 应用数学进展, 2016, 5(3): 321-326. https://dx.doi.org/10.12677/AAM.2016.53040

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