A general estimator for the right endpoint with an application to supercentenarian women's records

作者：Alves Isabel Fraga^*; Neves Claudia; Rosario Pedro

来源：Extremes, 2017, 20(1): 199-237.

DOI：10.1007/s10687-016-0260-6

• Extreme value theory
• Semi-parametric estimation
• Tail estimation
• Regular variation
• Monte Carlo simulation
• Human lifespan

We extend the setting of the right endpoint estimator introduced in Fraga Alves and Neves (Statist. Sinica 24, 1811-1835, 2014) to the broader class of light-tailed distributions with finite endpoint, belonging to some domain of attraction induced by the extreme value theorem. This stretch enables a general estimator for the finite endpoint, which does not require estimation of the (supposedly non-positive) extreme value index. A new testing procedure for selecting max-domains of attraction also arises in connection with the asymptotic properties of the general endpoint estimator. The simulation study conveys that the general endpoint estimator is a valuable complement to the most usual endpoint estimators, particularly when the true extreme value index stays above -1/2, embracing the most common cases in practical applications. An illustration is provided via an extreme value analysis of supercentenarian women data.

• 出版日期2017-3