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FUZZY REGRESSION TOWARDS A GENERAL INSURANCE APPLICATION
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  • FUZZY REGRESSION TOWARDS A GENERAL INSURANCE APPLICATION
  • FUZZY REGRESSION TOWARDS A GENERAL INSURANCE APPLICATION
저자명
Kim. Joseph H.T.,Kim. Joocheol
간행물명
Journal of applied mathematics & informatics
권/호정보
2014년|32권 3호|pp.343-357 (15 pages)
발행정보
한국전산응용수학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.