Tail product-limit process for truncated data with application to extreme value index estimation

2015/07/06 by Benchaira, Souad, Meraghni, Djamel, Necir, Abdelhakim · 2 citations
#FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.1507.01548

Abstract

A weighted Gaussian approximation to tail product-limit process for Pareto-like distributions of randomly right-truncated data is provided and a new consistent and asymptotically normal estimator of the extreme value index is derived. A simulation study is carried out to evaluate the finite sample behavior of the proposed estimator.

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• Robust and Smooth Estimation of the Extreme Tail Index via Weighted Minimum Density Power Divergence
• Nelson-Aalen kernel estimator to the tail index of right censored Pareto-type data

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