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모의실험을 이용한 경향성 분석기법의 검정력 평가

Power Test of Trend Analysis using Simulation Experiment

  • 류용준 (연세대학교 대학원 토목공학과) ;
  • 신홍준 (연세대학교 대학원 사회환경시스템공학부 토목환경공학과) ;
  • 김수영 (연세대학교 대학원 토목공학과) ;
  • 허준행 (연세대학교 사회환경시스템공학부 토목환경공학과)
  • 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.)
  • 투고 : 2012.08.01
  • 심사 : 2012.10.18
  • 발행 : 2013.03.31

초록

수문시계열 자료에 변동성, 도약성, 경향성, 주기성 등이 있으면 이러한 자료는 일반적으로 비정상성을 가지며, 특히 경향성 판단을 통한 다양한 방법들이 제시되어 왔다. 그러나 다양한 방법 간의 검정능력에 대한 평가는 많이 이루어지지 않았으며, 그로인해 동일 자료에 대한 다른 방법의 적용으로 반대의 결과가 나오는 경우도 발생하게 된다. 따라서 본 연구에서는 통계적 특성에 따른 경향성 분석의 변화를 파악하고, 경향성 분석방법 간의 검정능력을 파악해 보았다. 이를 위해 경향성 분석기법인 Mann-Kendall 검정, Hotelling-Pabst 검정, t 검정, Sen 검정을 적용하였으며 기울기, 표본크기, 표준편차에 따라 다양한 모의실험을 수행하였다. 그 결과 t 검정이 다른 검정에 비해 상대적으로 높은 검정력을 보였고, Mann-Kendall 검정, Hotelling-Pabst 검정, Sen 검정은 비슷한 결과를 보였다.

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.

키워드

참고문헌

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피인용 문헌

  1. The Recent Increasing Trends of Exceedance Rainfall Thresholds over the Korean Major Cities vol.34, pp.1, 2014, https://doi.org/10.12652/Ksce.2014.34.1.0117