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- Title
Monte Carlo Experiments on the Detection of Trends in Extreme Values.
- Authors
Xuebin Zhang; Zwiers, Francis W.; Guilong Li
- Abstract
Using Monte Carlo simulations, several methods for detecting a trend in the magnitude of extreme values are compared Ordinary least squares regression is found to be the least reliable method A Kendall's tau-based method provides some improvement The advantage of this method over that of least squares diminishes when the sample size is moderate to small Explicit consideration of the extreme value distribution when computing trend always outperforms the above two methods. The use of the r largest values as extremes enhances the power of detection lot moderate values of r the use of larger values of r may lead to bias in the magnitude of the estimated trend
- Subjects
MONTE Carlo method; SIMULATION methods &; models; CLIMATE research; WEATHER; METEOROLOGY
- Publication
Journal of Climate, 2004, Vol 17, Issue 10, p1945
- ISSN
0894-8755
- Publication type
Article
- DOI
10.1175/1520-0442(2004)017<1945:MCEOTD>2.0.CO;2