标题：A Monte Carlo Simulation Study Assessing the Performance of a Bayesian Approach for Identifying Differences in Change Point Location for Two Time Series
期刊名称：Journal of Statistical and Econometric Methods
印刷版ISSN：2241-0384
电子版ISSN：2241-0376
出版年度：2019
卷号：8
期号：3
页码：49-63
语种：English
出版社：Scienpress Ltd
摘要：Researchersin a variety of fields work with sequential data, such as measurements madeover time. In some instances, one ormore of the moments (e.g., mean, variance) of the series may change abruptly atsome point in the sequence, yielding what is known as a change point. There is a broad literature describingmethods for change point detection. Researchers working with multiple sequential series containing changepoints may be interested in comparing the locations of these changes. Recently, a method for comparing thelocations of 2 or more change points in 2 or more series using a Bayesianestimator has been described in the literature. The purpose of the current Monte Carlo simulation study was to extendthis earlier work by assessing the performance of this approach with timeseries of between 20 and 200 measurements in length, for a normally distributedmeasurement process. Results of thesimulation revealed that the method always controlled the Type I error rate,and had power of 0.75 or higher for series of 50 measurements or longer, whenthe variance in measurements was relatively low.
