Davison, A.C. and Ramesh, N.I. ORCID: https://orcid.org/0000-0001-6373-2557 (2000) Local likelihood smoothing of sample extremes. Journal of the Royal Statistical Society: Series B (Statistical Methodology, 62 (1). pp. 191-208. ISSN 1369-7412 (Print), 1467-9868 (Online) (doi:10.1111/1467-9868.00228)

Full text not available from this repository.

Abstract

Trends in sample extremes are of interest in many contexts, an example being environmental statistics. Parametric models are often used to model trends in such data, but they may not be suitable for exploratory data analysis. This paper outlines a semiparametric approach to smoothing example extremes, based on local polynomial fitting of the generalized extreme value distribution and related models. The uncertainty of fits is assessed by using resampling methods. The methods are applied to data on extreme temperatures and on record times for the womens 3000m race.

Item Type:	Article
Additional Information:	[1] Published on behalf of Royal Statistical Society.
Uncontrolled Keywords:	bootstrap, generalized extreme value distribution, local likelihood, local polynomial fitting, permutation test, temperature data
Subjects:	Q Science > QA Mathematics
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Department of Mathematical Sciences School of Computing & Mathematical Sciences > Statistics & Operational Research Group
Related URLs:	Publisher Publisher Organisation
Last Modified:	27 Oct 2020 14:50
URI:	http://gala.gre.ac.uk/id/eprint/368

Actions (login required)

View Item