USE OF CUMULATIVE SUMS OF SQUARES FOR RETROSPECTIVE DETECTION OF CHANGES OF VARIANCE
USE OF CUMULATIVE SUMS OF SQUARES FOR RETROSPECTIVE DETECTION OF CHANGES OF VARIANCE
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DOI：
10.2307/2290916
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发表时间：
1994-09-01
影响因子：
3.7
通讯作者：
TIAO, GC
中科院分区：
文献类型：
--
作者：
INCLAN, C;TIAO, GC
本文研究了独立观测序列方差中的多个变点问题。我们提出了一种基于迭代累积平方和（ICSS）算法来检测方差变化的方法。我们研究了中心化累积平方和函数的性质，并为ICSS算法提供了一个直观的基础。对于中等规模的序列（即200个及以上观测值），ICSS算法提供的结果与贝叶斯方法或似然比检验所获得的结果相当，且没有这些方法所需的沉重计算负担。文中给出了将ICSS算法与其他方法进行比较的模拟结果。
This article studies the problem of multiple change points in the variance of a sequence of independent observations. We propose a procedure to detect variance changes based on an iterated cumulative sums of squares (ICSS) algorithm. We study the properties of the centered cumulative sum of squares function and give an intuitive basis for the ICSS algorithm. For series of moderate size (i.e., 200 observations and beyond), the ICSS algorithm offers results comparable to those obtained by a Bayesian approach or by likelihood ratio tests, without the heavy computational burden required by these approaches. Simulation results comparing the ICSS algorithm to other approaches are presented.