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保险中小样本信息处理的非均匀信息扩散法
引用本文:忻莉莉,耿辉,王永民,张晶晶.保险中小样本信息处理的非均匀信息扩散法[J].上海大学学报(英文版),2007,11(3):259-262.
作者姓名:忻莉莉  耿辉  王永民  张晶晶
作者单位:Department of Mathematics College of Sciences,Shanghai University,Shanghai 200444,P. R. China,Department of Mathematics,College of Sciences,Shanghai University,Shanghai 200444,P. R. China,Department of Mathematics,College of Sciences,Shanghai University,Shanghai 200444,P. R. China,Department of Mathematics,College of Sciences,Shanghai University,Shanghai 200444,P. R. China
摘    要:When analyzing and evaluating risks in insurance, people are often confronted with the situation of incomplete information and insufficient data, which is known as a small-sample problem. In this paper, a one-dimensional small-sample problem in insurance was investigated using the kernel density estimation method (KerM) and general limited information diffusion method (GIDM). In particular, MacCormack technique was applied to get the solutions of GIDM equations and then the optimal diffusion solution was acquired based on the two optimization principles. Finally, the analysis introduced in this paper was verified by treating some examples and satisfying results were obtained.

关 键 词:保险  信息分析  模糊数学  核密度估算  麦克柯麦科技术  小样分析  有限信息
文章编号:10.1007/s11741-007-0314-2
收稿时间:26 September 2005
修稿时间:2005-09-262005-12-06

General limited information diffusion method of small-sample information analysis in insurance
XIN Li-li,GENG Hui,WANG Yong-min,ZHANG Jing-jing.General limited information diffusion method of small-sample information analysis in insurance[J].Journal of Shanghai University(English Edition),2007,11(3):259-262.
Authors:XIN Li-li  GENG Hui  WANG Yong-min  ZHANG Jing-jing
Institution:Department of Mathematics,College of Sciences,Shanghai University,Shanghai 200444,P.R.China
Abstract:When analyzing and evaluating risks in insurance, people are often confronted with the situation of incomplete information and insufficient data, which is known as a small-sample problem. In this paper, a one-dimensional small-sample problem in insurance was investigated using the kernel density estimation method (KerM) and general limited information diffusion method (GIDM). In particular, MacCormack technique was applied to get the solutions of GIDM equations and then the optimal diffusion solution was acquired based on the two optimization principles. Finally, the analysis introduced in this paper was verified by treating some examples and satisfying results were obtained.
Keywords:fuzzy mathematics  kernel density estimation  information diffusion  MacCormack technique  small-sample
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