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• W2347027447 abstract "ABSTRACTMotivated by insurance applications, a mixed Poisson cluster model is considered, where the cluster center process is a mixed Poisson process and descendant processes are additive processes. Each point of the center process represents a claim’s reported time and descendant processes are interpreted as processes of the corresponding payments or number of payments. In this study, we focus on the process aggregating all separate claim’s payment processes. Given the past observations, we study prediction of future increments and their mean-squared errors, also revealing the dependency between future increments from non-reported (IBNR) claims and the past available information. In the existing literature, they are independent since models were considered with a purely Poissonian center process. We derive computationally reasonable expressions for predictors and their variances." @default.
• W2347027447 created "2016-06-24" @default.
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• W2347027447 date "2016-05-09" @default.
• W2347027447 modified "2023-09-22" @default.
• W2347027447 title "Prediction in a mixed Poisson cluster model" @default.
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• W2347027447 doi "https://doi.org/10.1080/15326349.2016.1170614" @default.
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