English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper we consider the semi-parametric estimation of extreme quantilesof a right heavy-tail model. We propose a new Log Probability Weighted Momentestimator for extreme quantiles, which is obtained from the estimators of theshape and scale parameters of the tail. Under a second-order regular variationcondition on the tail, of the underlying distribution function, we deduce thenon degenerate asymptotic behaviour of the estimators under study and presentan asymptotic comparison at their optimal levels. In addition, the performanceof the estimators is illustrated through an application to real data.

A Log Probability Weighted Moment Estimator of Extreme Quantiles