Nonparametric estimation of the conditional tail index and extreme quantiles under random censoring

DOI10.1016/j.csda.2014.05.007zbMath1506.62134OpenAlexW2053278527WikidataQ59245352 ScholiaQ59245352MaRDI QIDQ1623653

Pathé Ndao, Jean-François Dupuy, Aliou Diop

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.05.007

zbMATH Keywords

heavy-tailed distributionsimulationsconditional extreme quantilesmoving windowconditional extreme value index

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Statistics of extreme values; tail inference (62G32)

Related Items

Quantile regression for panel data models with fixed effects under random censoring, On the study of extremes with dependent random right-censoring, Nonparametric estimation of the conditional extreme-value index with random covariates and censoring, Estimating the conditional extreme-value index under random right-censoring, Tail and quantile estimation for real-valued \(\beta\)-mixing spatial data, Estimation of extreme survival probabilities with cox model, Local robust estimation of Pareto-type tails with random right censoring, Estimation of extremes for Weibull-tail distributions in the presence of random censoring, On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails, Trimmed extreme value estimators for censored heavy-tailed data, Estimation of the extreme value index in a censorship framework: asymptotic and finite sample behavior, Bias-corrected estimation for conditional Pareto-type distributions with random right censoring, Estimation of extremes for heavy-tailed and light-tailed distributions in the presence of random censoring

Uses Software

• R
• MASS (R)

Cites Work

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