Robust conditional Weibull-type estimation

Yuri Goegebeur, Armelle Guillou, Theo Rietsch

Research output: Contribution to journalJournal articleResearchpeer-review


We study nonparametric robust tail coefficient estimation when the variable of interest, assumed to be of Weibull type, is observed simultaneously with a random covariate. In particular, we introduce a robust estimator for the tail coefficient, using the idea of the density power divergence, based on the relative excesses above a high threshold. The main asymptotic properties of our estimator are established under very general assumptions. The finite sample performance of the proposed procedure is evaluated by a small simulation experiment.

Original languageEnglish
JournalAnnals of the Institute of Statistical Mathematics
Issue number3
Pages (from-to)479-514
Publication statusPublished - 2015


  • Density power divergence
  • Local estimation
  • Tail coefficient
  • Weibull-type distribution


Dive into the research topics of 'Robust conditional Weibull-type estimation'. Together they form a unique fingerprint.

Cite this