Semi-parametric tail inference through probability-weighted moments |
| |
Authors: | Frederico Caeiro M Ivette Gomes |
| |
Institution: | a New University of Lisbon and CMA, Faculdade de Ciências e Tecnologia, 2829-516 Caparica, Portugal b University of Lisbon, DEIO and CEAUL, Faculdade de Ciências, Campo Grande, 1749-016 Lisboa, Portugal |
| |
Abstract: | In this paper, for heavy-tailed models, and working with the sample of the k largest observations, we present probability weighted moments (PWM) estimators for the first order tail parameters. Under regular variation conditions on the right-tail of the underlying distribution function F we prove the consistency and asymptotic normality of these estimators. Their performance, for finite sample sizes, is illustrated through a small-scale Monte Carlo simulation. |
| |
Keywords: | Heavy tails Extreme value index First order scale parameter Semi-parametric estimation Statistics of extremes |
本文献已被 ScienceDirect 等数据库收录! |
|