Ramesh, N.I. ORCID: 0000-0001-6373-2557 and Davison, A.C. (2001) Local models for exploratory analysis of hydrological extremes. Journal of Hydrology, 256 (1-2). pp. 106-119. ISSN 0022-1694 (doi:https://doi.org/10.1016/S0022-1694(01)00522-4)

Full text not available from this repository.

Abstract

Trend analysis is widely used for detecting changes in hydrological data. Parametric methods for this employ pre-specified models and associated tests to assess significance, whereas non-parametric methods generally apply rank tests to the data. Neither approach is suitable for exploratory analysis, because parametric models impose a particular, perhaps unsuitable, form of trend, while testing may confirm that trend is present but does not describe its form. This paper describes semi-parametric approaches to trend analysis using local likelihood fitting of annual maximum and partial duration series and illustrates their application to the exploratory analysis of changes in extremes in sea level and river flow data. Bootstrap methods are used to quantify the variability of estimates.

Item Type:	Article
Uncontrolled Keywords:	annual maximum method, bootstrap, generalized extreme-value distribution, generalized Pareto distribution, local likelihood, partial duration series
Subjects:	Q Science > QA Mathematics T Technology > TC Hydraulic engineering. Ocean engineering
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 Organisation
Last Modified:	27 Oct 2020 14:50
URI:	http://gala.gre.ac.uk/id/eprint/572

Actions (login required)

View Item