Comparison of performance between rescaled range analysis and rescaled variance analysis in detecting abrupt dynamic change

doi:10.1088/1674-1056/24/4/049205

Abstract In the present paper, a comparison of the performance between moving cutting data-rescaled range analysis (MC-R/S) and moving cutting data-rescaled variance analysis (MC-V/S) is made. The results clearly indicate that the operating efficiency of the MC-R/S algorithm is higher than that of the MC-V/S algorithm. In our numerical test, the computer time consumed by MC-V/S is approximately 25 times that by MC-R/S for an identical window size in artificial data. Except for the difference in operating efficiency, there are no significant differences in performance between MC-R/S and MC-V/S for the abrupt dynamic change detection. MC-R/S and MC-V/S both display some degree of anti-noise ability. However, it is important to consider the influences of strong noise on the detection results of MC-R/S and MC-V/S in practical application processes.

Keywords: moving cutting data-rescaled range analysis moving cutting data-rescaled variance analysis abrupt dynamic change

Received: 12 September 2014
Revised: 30 October 2014
Accepted manuscript online:

PACS:	92.70.Aa	(Abrupt/rapid climate change)
	95.10.Fh	(Chaotic dynamics)

Fund: Project supported by the National Basic Research Program of China (Grant No. 2012CB955902) and the National Natural Science Foundation of China (Grant Nos. 41275074, 41475073, and 41175084).

Corresponding Authors: He Wen-Ping
E-mail: wenping_he@163.com

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He Wen-Ping (何文平), Liu Qun-Qun (刘群群), Jiang Yun-Di (姜允迪), Lu Ying (卢莹) Comparison of performance between rescaled range analysis and rescaled variance analysis in detecting abrupt dynamic change 2015 Chin. Phys. B 24 049205

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Comparison of performance between rescaled range analysis and rescaled variance analysis in detecting abrupt dynamic change

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