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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제10권 제3호
- 발행연도
- 2008.1
- 수록면
- 1,239 - 1,245 (7page)
이용수
초록· 키워드
오류제보하기
The generalized extreme value distribution(GEVD) is used to estimate the extreme events of natural phenomena. Likelihood based inference are discussed. Despite of having some pleasant features of maximum likelihood estimator it also has some disadvantages over small sample while dealing with negative shape parameter. This limitation has solved by imposing penalty function on likelihood equation. In this study we try to show that, instead of using an overall hyper-parameter to the penalized likelihood function. Data adaptive estimation procedure is introduced to selecting hyper parameter and to observe the performance of the penalty functions as well as with maximum likelihood estimator. Some of the rainfall data sets of South Korea are discussed.
목차
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참고문헌 (9)
참고문헌 신청
Castillo E. / 2005 / Extreme Value and Related Models with Applications in Engineering and Science / Wiley-Interscience
Coles S. / 1999 / Likelihood-based inference for extreme value models / Extremes 2 : 5 ~ 23
Coles S. / 2001 / An Introduction to Statistical Modeling of Extreme Values / Springer-Verlag
KMA / / Korea Meteorological Administration
Martin E. S. / 2000 / Generalized maximum likelihood generalized extreme-value quantile estimators for hydrologic data / Water Resources Research 36 (3) : 737 ~ 744
Coles S. / 1999 / Likelihood-based inference for extreme value models / Extremes 2 : 5 ~ 23
Coles S. / 2001 / An Introduction to Statistical Modeling of Extreme Values / Springer-Verlag
KMA / / Korea Meteorological Administration
Martin E. S. / 2000 / Generalized maximum likelihood generalized extreme-value quantile estimators for hydrologic data / Water Resources Research 36 (3) : 737 ~ 744
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