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http://dx.doi.org/10.3741/JKWRA.2017.50.4.253

A study on a tendency of parameters for nonstationary distribution using ensemble empirical mode decomposition method  

Kim, Hanbeen (School of Civil and Environmental Engineering, Yonsei University)
Kim, Taereem (School of Civil and Environmental Engineering, Yonsei University)
Shin, Hongjoon (University-Industry Foundation, Yonsei University)
Heo, Jun-Haeng (School of Civil and Environmental Engineering, Yonsei University)
Publication Information
Journal of Korea Water Resources Association / v.50, no.4, 2017 , pp. 253-261 More about this Journal
Abstract
A lot of nonstationary frequency analyses have been studied in recent years as the nonstationarity occurs in hydrologic time series data. In nonstationary frequency analysis, various forms of probability distributions have been proposed to consider the time-dependent statistical characteristics of nonstationary data, and various methods for parameter estimation also have been studied. In this study, we aim to introduce a parameter estimation method for nonstationary Gumbel distribution using ensemble empirical mode decomposition (EEMD); and to compare the results with the method of maximum likelihood. Annual maximum rainfall data with a trend observed by Korea Meteorological Administration (KMA) was applied. As a result, both EEMD and the method of maximum likelihood selected an appropriate nonstationary Gumbel distribution for linear trend data, while the EEMD selected more appropriate nonstationary Gumbel distribution than the method of maximum likelihood for quadratic trend data.
Keywords
Ensemble empirical mode decomposition; Method of maximum likelihood; Nonstationary Gumbel distribution; Parameter estimation;
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