Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Goodness-of-fit test for the gumbel distribution based on the generalized Lorenz curve

일반화된 로렌츠 곡선을 기반으로 한 Gumbel 분포의 적합도 검정

  • Lee, Kyeongjun (Department of Computer Science and Statistics, Daegu University)
  • 이경준 (대구대학교 전산통계학과)
  • Received : 2017.06.29
  • Accepted : 2017.07.13
  • Published : 2017.07.31
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Abstract

There are many areas of applications where Gumbel distribution are employed such as environmental sciences, system reliability and hydrology. The goodness-of-fit test for Gumbel distribution is very important in environmental sciences, system reliability and hydrology data analysis. Therefore, we propose the two test statistics to test goodness-of-fit for the Gumbel distribution based on the generalized Lorenz curve. We compare the new test statistic with the Anderson - Darling test, Cramer - vonMises test, and modified Anderson - Darling test in terms of the power of the test through by Monte Carlo method. As a result, the new test statistics are more powerful than the other test statistics. Also, we propose new graphic method to goodness-of-fit test for the Gumbel distribution based on the generalized Lorenz curve.

통계학에서 사용되어지고 있는 Gumbel 분포는 환경과학, 시스템 신뢰성, 수문학과 같은 분야에서 많이 응용되고 있다. 따라서 환경과학, 시스템 신뢰성, 수문학과 관련된 자료를 분석함에 있어서 분석에 사용되어지는 자료가 Gumbel 분포를 따르는지 확인하는 것은 매우 중요하다. 이를 확인하기 위해 본 논문에서는 새로운 두 가지의 Gumbel 분포의 적합도 검정통계량을 일반화된 로렌츠 곡선을 기반으로 하여 제안하였고, Anderson - Darling 검정, Cramer - vonMises 검정, 수정된 Anderson - Darling 검정과 비교하였다. 그 결과 새롭게 제안한 검정통계량은 기존의 검정방법에 비하여 우수한 것을 확인할 수 있었다. 또한 새롭게 제안한 변형된 표본 일반화된 로렌츠 곡선을 이용하여 두 가지의 새로운 적합도 검정 그래프 방법을 제안하였고, 새롭게 제안된 그래프를 통하여 손쉽게 데이터가 Gumbel 분포를 따르는지를 파악 할 수 있었다. 또한 호주 시드니의 연간 일 최대 강수량 자료를 사용하여 새롭게 제안한 검정 통계량과 그래프 방법을 이용하여 적용해 보았다.

Keywords

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