Data Adaptive Estimation in Generalized Extreme Value Distribution

• 발행기관: 한국자료분석학회
• 저자명: Md. Sharwar Murshed 박정수(Jeong Soo Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.10 No.3, 1239~1245쪽, 전체 7쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2008.06.30

영문 초록

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

1. Introduction

2. Generalized extreme value distribution and rainfall data

3. Maximum likelihood estimation and penalty functions

4. Data adaptive estimation and selected hyper-parameters

5. Concluding remarks

References

키워드

Bias correction Hyper-parameter Likelihood based inference Penalty function