Power Test of Trend Analysis using Simulation Experiment

모의실험을 이용한 경향성 분석기법의 검정력 평가

  • Ryu, Yongjun (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Shin, Hongjoon (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Kim, Sooyoung (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Heo, Jun-Haeng (School of Civil and Environmental Engineering, Yonsei Univ.)
  • 류용준 (연세대학교 대학원 토목공학과) ;
  • 신홍준 (연세대학교 대학원 사회환경시스템공학부 토목환경공학과) ;
  • 김수영 (연세대학교 대학원 토목공학과) ;
  • 허준행 (연세대학교 사회환경시스템공학부 토목환경공학과)
  • Received : 2012.08.01
  • Accepted : 2012.10.18
  • Published : 2013.03.31


Time series data including change, jump, trend and periodicity generally have nonstationarity. Especially, various methods have been proposed to identify the trend about hydrological time series data. However, among various methods, evaluation about capability of each trend test has not been done a lot. Even for the same data, each method may show the different result. In this study, the simulation was performed for identification about the changes in trend analysis according to the statistical characteristics and the capability in the trend analysis. For this purpose, power test for the trend analysis is conducted using Men-Kendall test, Hotelling-Pabst test, t test and Sen test according to the slope, sample size, standard deviation and significance level. As a result, t test has higher statistical power than the others, while Mann-Kendall, Hotelling-Pabst, and Sen tests were similar results.


Supported by : 한국건설교통기술평가원


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