Estimation of a tail index based on minimum density power divergence

DOI10.1016/J.JMVA.2008.02.031zbMath1151.62321OpenAlexW2032078650MaRDI QIDQ957324

Moosup Kim, Sangyeol Lee

Publication date: 27 November 2008

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2008.02.031

zbMATH Keywords

outliersrobustnesstail indexminimum density power divergence estimatorstrong mixing processes

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09) Statistics of extreme values; tail inference (62G32)

Related Items (12)

Robust and bias-corrected estimation of the probability of extreme failure sets ⋮ Divergence based robust estimation of the tail index through an exponential regression model ⋮ Robust nonparametric estimation of the conditional tail dependence coefficient ⋮ Dual divergence estimators of the tail index ⋮ Robust estimator of conditional tail expectation of Pareto-type distribution ⋮ Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions ⋮ The Minimum Density Power Divergence Estimation for the Lognormal Density ⋮ Local robust estimation of Pareto-type tails with random right censoring ⋮ Local robust and asymptotically unbiased estimation of conditional Pareto-type tails ⋮ Robust conditional Weibull-type estimation ⋮ Robust estimation of Pareto-type tail index through an exponential regression model ⋮ On the tail index inference for heavy-tailed GARCH-type innovations

Cites Work

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• A robust estimator for the tail index of Pareto-type distributions
• Extremes and related properties of random sequences and processes
• On tail index estimation using dependent data
• A simple general approach to inference about the tail of a distribution
• Minimum Hellinger distance estimates for parametric models
• Estimating a tail exponent by modelling departure from a Pareto distribution
• Test for parameter change based on the estimator minimizing density-based divergence meas\-ures
• Minimum Hellinger Distance Estimation for Multivariate Location and Covariance
• SLOW VARIATION WITH REMAINDER: THEORY AND APPLICATIONS
• Uniform rates of convergence in extreme-value theory
• On the Strong Mixing Property for Linear Sequences
• Robust and efficient estimation by minimising a density power divergence
• Asymptotic behavior of hill's estimator for autoregressive data
• Consistency of Hill's estimator for dependent data

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