Weak convergence of a bootstrap geometric-type estimator with applications to risk theory

DOI10.1016/j.insmatheco.2005.12.002zbMath1123.62032OpenAlexW1970445372MaRDI QIDQ2499834

Ana Cristina Moreira Freitas, Margarida Brito

Publication date: 14 August 2006

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.insmatheco.2005.12.002

zbMATH Keywords

bootstrapparameter estimationrandom walkadjustment coefficientSparre Andersen model

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09)

Related Items (2)

Consistent estimation of the tail index for dependent data ⋮ Edgeworth expansion for an estimator of the adjustment coefficient

Uses Software

• bootstrap

Cites Work

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• On the estimation of the adjustment coefficient in risk theory via intermediate order statistics
• On asymptotic normality of Hill's estimator for the exponent of regular variation
• Some asymptotic theory for the bootstrap
• A bootstrap procedure for estimating the adjustment coefficients
• A simple general approach to inference about the tail of a distribution
• Bootstrap methods: another look at the jackknife
• A tail bootstrap procedure for estimating the tail Pareto-index
• Asymptotic normality of least-squares estimators of tail indices
• Limiting behaviour of a geometric-type estimator for tail indices.
• Almost sure convergence of the Hill estimator
• On Some alternative estimates of the adjustment coefficient in risk theory
• Confidence bounds for the adjustment coefficient
• Extreme Values in the GI/G/1 Queue

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