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Change-Points Detections for Interrupted Time Series Analysis: A Literature Review

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Abstract:

General review of Change-Points detection methods applied in Interrupted Time Series Analysis for recent years. Articles from domains like meteorology, hydrology, stock analysis, sequences mining et al. are compared together. The literatures range from the 1980s to 2013. The methods are generally classified in Parametric, Semi-Parametric, and Nonparametric. Some non-statistical methods are also mentioned in this review. Characters of each method are briefly summarized. As all methods mentioned in this review share a common purpose that to detect change-points, most of them can be used in other domains after some proper adjustment.

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Periodical:

Applied Mechanics and Materials (Volumes 462-463)

Pages:

187-192

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.462-463.187

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Online since:

November 2013

Authors:

Jing Bo Chen, Jun Bao Zheng*, Lei Yang, Ya Ming Wang

Keywords:

Nonparametric, Parametric, Parametric and Nonparametric, Segmentation, Statistics, Trend Analysis

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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