Robust estimation of the Pickands dependence function under random right censoring

Yuri Goegebeur*, Armelle Guillou, Jing Qin

*Kontaktforfatter for dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

30 Downloads (Pure)

Abstrakt

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.

OriginalsprogEngelsk
TidsskriftInsurance: Mathematics and Economics
Vol/bind87
Sider (fra-til)101-114
ISSN0167-6687
DOI
StatusUdgivet - 1. jul. 2019

Fingeraftryk

Dyk ned i forskningsemnerne om 'Robust estimation of the Pickands dependence function under random right censoring'. Sammen danner de et unikt fingeraftryk.

Citationsformater