Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing
분야
자연과학 > 통계학
저자
( Myung Joon Kim ) , ( Yeong Hwa Kim )
발행기관
한국통계학회
간행물정보
CSAM(Communications for Statistical Applications and Methods) 2013년, 제20권 제4호, 321~327페이지(총7페이지)
파일형식
02706322.pdf [무료 PDF 뷰어 다운로드]
  • ※ 본 자료는 참고용 논문으로 수정 및 텍스트 복사가 되지 않습니다.
  • 구매가격
    4,500원
    적립금
    135원 (구매자료 3% 적립)
    이메일 발송  스크랩 하기
    자료 다운로드  네이버 로그인
    영문초록
    Bayesian and empirical Bayesian methods have become quite popular in the theory and practice of statistics. However, the objective is to often produce an ensemble of parameter estimates as well as to produce the histogram of the estimates. For example, in insurance pricing, the accurate point estimates of risk for each group is necessary and also proper dispersion estimation should be considered. Well-known Bayes estimates (which is the posterior means under quadratic loss) are underdispersed as an estimate of the histogram of parameters. The adjustment of Bayes estimates to correct this problem is known as constrained Bayes estimators, which are matching the first two empirical moments. In this paper, we propose a way to apply the constrained Bayes estimators in insurance pricing, which is required to estimate accurately both location and dispersion. Also, the benefit of the constrained Bayes estimates will be discussed by analyzing real insurance accident data.
    사업자등록번호 220-87-87785 대표.신현웅 주소.서울시 서초구 방배로10길 18, 402호 대표전화.070-8809-9397
    개인정보책임자.박정아 통신판매업신고번호 제2017-서울서초-1765호 이메일 help@reportshop.co.kr
    copyright (c) 2009 happynlife. steel All reserved.