Estimating the Mean of Heavy-tailed Distribution under Random Truncation

DOI10.17516/1997-1397-2021-14-3-273-286OpenAlexW3180357294MaRDI QIDQ5071348

Ben Dahmane Khanssa, Brahimi Brahim, Benatia Fateh

Publication date: 21 April 2022

Published in: Journal of Siberian Federal University. Mathematics & Physics (Search for Journal in Brave)

Full work available at URL: http://mathnet.ru/eng/jsfu913

zbMATH Keywords

heavy-tailed distributionsHill estimatorLynden-Bell estimatorrandom truncation

Mathematics Subject Classification ID

Stochastic processes (60Gxx) Nonparametric inference (62Gxx) Limit theorems in probability theory (60Fxx)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Tail product-limit process for truncated data with application to extreme value index estimation
• Kernel estimation of the tail index of a right-truncated Pareto-type distribution
• Weighted approximations of tail copula processes with application to testing the bivariate extreme value condition
• The central limit theorem under random truncation
• Limit theorems for tail processes with application to intermediate quantile estimation
• The central limit theorem under random censorship
• A bias-reduced estimator for the mean of a heavy-tailed distribution with an infinite second moment
• Estimating extreme quantiles under random truncation
• Approximations to the tail empirical distribution function with application to testing extreme value conditions
• Heavy-Tail Phenomena
• Estimating a distribution function with truncated data
• Estimating the mean of a heavy tailed distribution

This page was built for publication: Estimating the Mean of Heavy-tailed Distribution under Random Truncation