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Article | 05-September-2021

Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss

The article presents a collective risk model for the insurance claims. The objective is to estimate a premium, which is defined as a functional specified up to unknown parameters. For this purpose, the Bayesian methodology, which combines the prior knowledge about certain unknown parameters with the knowledge in the form of a random sample, has been adopted. The generalised Bregman loss function is considered. In effect, the results can be applied to numerous loss functions, including the

Agata Boratyńska

Statistics in Transition New Series, Volume 22 , ISSUE 3, 123–140

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