Robust estimation of the extreme value index of Pareto-type distributions under random truncation with applications

Autor:	Brahimi Brahim, Zahnit Abida, Yahia Djabrane
Rok vydání:	2021
Předmět:	Statistics and Probability Estimation Truncation Modeling and Simulation Pareto principle Applied mathematics Extreme value index Management Science and Operations Research Statistics Probability and Uncertainty Type (model theory) Mathematics
Zdroj:	Pakistan Journal of Statistics and Operation Research. :235-245
ISSN:	2220-5810 1816-2711
DOI:	10.18187/pjsor.v17i1.2735
Popis:	In this paper, we introduce a new robust estimator for the extreme value index of Pareto-type distributions under randomly right-truncated data and establish its consistency and asymptotic normality. Our considerations are based on the Lynden-Bell integral and a useful huberized M-functional and M-estimators of the tail index. A simulation study is carried out to evaluate the robustness and the nite sample behavior of the proposed estimator. Extreme quantiles estimation is also derived and applied to real data-set of lifetimes of automobile brake pads.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f4bb7a55006fce2cdbba6c9aa1d44fd7 https://doi.org/10.18187/pjsor.v17i1.2735 Zobrazit plný text záznamu