Unified Extreme-Value Distribution
This article has been corrected.
VIEW CORRECTIONPublication: Journal of Irrigation and Drainage Engineering
Volume 143, Issue 12
Abstract
A new unified extreme-value (UEV) distribution is proposed that combines EV-1 (Gumbel), EV-2 (Frechet), and EV-3 (Weibull) distributions to better replace the generalized extreme-value (GEV) distribution in that sense. Two simple methods, one graphical and other objective, are devised for estimating parameters of the new UEV, with the diagnostic property of identifying the concerned extreme-value distribution implicitly from the data series used. Its application on illustrative examples suggests an ease of application, reliable estimates of parameters, full transparency in the estimation process, and outperformance of widely used computationally and mathematically more complex methods, e.g., method of moments, maximum likelihood, and probability weighted moments, on GEV and EV distributions, resulting in savings of time and resources. Parameter determination and application of the UEV distribution can even be worked out on a spreadsheet. A new concept and quantification of a deterministic confidence limit is also proposed for its easy application to avoid and replace the tedious process with statistical hypothesis-testing involved in the currently used probabilistic confidence interval. The new UEV, estimation methods, and deterministic confidence limit will be of help to field engineers and practitioners.
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Journal of Irrigation and Drainage Engineering
Volume 143 • Issue 12 • December 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: May 27, 2016
Accepted: May 2, 2017
Published online: Sep 22, 2017
Published in print: Dec 1, 2017
Discussion open until: Feb 22, 2018
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