Tree-based censored regression with applications in insurance

Olivier Lopez (), Xavier Milhaud () and Pierre-Emmanuel Thérond
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Olivier Lopez: LSTA - Laboratoire de Statistique Théorique et Appliquée - UPMC - Université Pierre et Marie Curie - Paris 6 - CNRS - Centre National de la Recherche Scientifique
Xavier Milhaud: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon

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Abstract: We propose a regression tree procedure to estimate the conditional distribution of a variable which is not directly observed due to censoring. The model that we consider is motivated by applications in insurance , including the analysis of guarantees that involve durations, and claim reserving. We derive consistency results for our procedure, and for the selection of an optimal subtree using a pruning strategy. These theoretical results are supported by a simulation study, and two applications involving insurance datasets. The first concerns income protection insurance, while the second deals with reserving in third-party liability insurance.

Keywords: Survival analysis; censoring; regression tree; model selection; insurance; CART (search for similar items in EconPapers)
Date: 2016-09-12
Note: View the original document on HAL open archive server: https://hal.science/hal-01141228v2
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Citations: View citations in EconPapers (8)

Published in Electronic Journal of Statistics , 2016, 10 (2), pp.2685-2716. ⟨10.1214/16-EJS1189⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01141228

DOI: 10.1214/16-EJS1189

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