Robust estimation of the Pickands dependence function under random right censoring

Yuri Goegebeur, Armelle Guillou and Jing Qin

Insurance: Mathematics and Economics, 2019, vol. 87, issue C, 101-114

Abstract: We consider robust nonparametric estimation of the Pickands dependence function under random right censoring. The estimator is obtained by applying the minimum density power divergence criterion to properly transformed bivariate observations. The asymptotic properties are investigated by making use of results for Kaplan–Meier integrals. We investigate the finite sample properties of the proposed estimator with a simulation experiment and illustrate its practical applicability on a dataset of insurance indemnity losses.

Keywords: Pickands dependence function; Censoring; Kaplan–Meier integral; Density power divergence; Insurance indemnity losses (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:87:y:2019:i:c:p:101-114

DOI: 10.1016/j.insmatheco.2019.03.008

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