Dynamic credibility with outliers and missing observations

IF 0.6 4区 数学 Q4 MATHEMATICS, APPLIED Applications of Mathematics Pub Date : 1996-01-01 DOI:10.21136/AM.1996.134318
T. Cipra
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引用次数: 5

Abstract

In actuarial practice the credibility models must face the problem of outliers and missing observations. If using the $M$-estimation principle from robust statistics in combination with Kalman filtering one obtains the solution of this problem that is acceptable in the numerical framework of the practical actuarial credibility. The credibility models are classified as static and dynamic in this paper and the shrinkage is used for the final ratemaking.
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具有异常值和缺失观测值的动态可信度
在精算实践中,可信度模型必须面对异常值和缺失观测值的问题。如果将稳健统计中的$M$估计原理与卡尔曼滤波相结合,就可以得到这个问题在实际精算可信度的数值框架中可以接受的解。本文将可信度模型分为静态可信度模型和动态可信度模型,并采用收缩率来确定最终的可信度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applications of Mathematics
Applications of Mathematics 数学-应用数学
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
3.0 months
期刊介绍: Applications of Mathematics publishes original high quality research papers that are directed towards applications of mathematical methods in various branches of science and engineering. The main topics covered include: - Mechanics of Solids; - Fluid Mechanics; - Electrical Engineering; - Solutions of Differential and Integral Equations; - Mathematical Physics; - Optimization; - Probability Mathematical Statistics. The journal is of interest to a wide audience of mathematicians, scientists and engineers concerned with the development of scientific computing, mathematical statistics and applicable mathematics in general.
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