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Derivation of Probability Plot Correlation Coefficient Test Statistics and Regression Equation for the GEV Model based on L-moments

L-모멘트 법 기반의 GEV 모형을 위한 확률도시 상관계수 검정 통계량 유도 및 회귀식 산정

  • Ahn, Hyunjun (Civil and Environmental Engineering, Yonsei University) ;
  • Jeong, Changsam (Civil and Environmental Engineering, Induk University) ;
  • Heo, Jun-Haeng (Civil and Environmental Engineering, Yonsei University)
  • 안현준 (연세대학교 대학원 토목환경공학과 통합과정) ;
  • 정창삼 (인덕대학교 토목환경공학과) ;
  • 허준행 (연세대학교 사회환경공학부 토목환경공학과)
  • Received : 2020.02.07
  • Accepted : 2020.02.28
  • Published : 2020.03.31

Abstract

One of the important problem in statistical hydrology is to estimate the appropriated probability distribution for a given sample data. For the problem, a goodness-of-fit test is conducted based on the similarity between estimated probability distribution and assumed theoretical probability distribution. Probability plot correlation coefficient test (PPCC) is one of the goodness-of-fit test method. PPCC has high rejection power and its application is simple. In this study, test statistics of PPCC were derived for generalized extreme value distribution (GEV) models based on L-moments and these statistics were suggested by the multiple and nonlinear regression equations for its usability. To review the rejection power of the newly proposed method in this study, Monte Carlo simulation was performed with other goodness-of-fit tests including the existing PPCC test. The results showed that PPCC-A test which is proposed in this study demonstrated better rejection power than other methods, including the existing PPCC test. It is expected that the new method will be helpful to estimate the appropriate probability distribution model.

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