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Bayesian ratemaking with common effects modeled by mixture of Polya tree processes

机译:通过混合波利亚树过程建模的具有共同效应的贝叶斯速率生成

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摘要

In classical models for Bayesian ratemaking, claims are usually assumed to be independent over risks. However, this assumption may be violated because there are situations that could derive possible dependence among the insured individuals. This paper aims to investigate the typical problem of experience ratemaking to account for a special type of dependence that is known as common effects in the literature. Polya tree processes are employed to model the common effects and, by means of an MCMC scheme, the corresponding Bayesian premiums are numerically computed. This provides a useful alternative to the well known results on Bayesian ratemaking with common effects. (C) 2018 Elsevier B.V. All rights reserved.
机译:在贝叶斯利率制定的经典模型中,通常假定索赔独立于风险。但是,此假设可能会被违反,因为在某些情况下,被保险人之间可能会产生依赖性。本文旨在研究经验率估算的典型问题,以解释一种特殊类型的依赖性,这在文献中被称为常见效应。使用Polya树过程对常见效果进行建模,并通过MCMC方案对相应的贝叶斯溢价进行数值计算。这提供了对具有常见效果的贝叶斯速率估算的众所周知结果的有用替代方法。 (C)2018 Elsevier B.V.保留所有权利。

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