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Comparison of Nonstationary Generalized Logistic Models Based on Monte Carlo Simulation : Volume 371, Issue 371 (12/06/2015)

By Kim, S.

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Book Id: WPLBN0004021442
Format Type: PDF Article :
File Size: Pages 4
Reproduction Date: 2015

Title: Comparison of Nonstationary Generalized Logistic Models Based on Monte Carlo Simulation : Volume 371, Issue 371 (12/06/2015)  
Author: Kim, S.
Volume: Vol. 371, Issue 371
Language: English
Subject: Science, Proceedings, International
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Heo, J., Kim, S., Kim, T., Ahn, H., & Nam, W. (2015). Comparison of Nonstationary Generalized Logistic Models Based on Monte Carlo Simulation : Volume 371, Issue 371 (12/06/2015). Retrieved from

Description: School of Civil and Environmental engineering, Yonsei University, Korea. Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold) data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.

Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

Fisher, R. A.: On the mathematical foundations of theoretical statistics, Philos. Trans. Roy. Soc. London Ser. A, 222, 309–368, 1922.; Hosking, J. R. M. and Wallis, J. R.: Regional frequency analysis: an approach based on L-moments, Cambridge University Press, 1997.; Institute of Hydrology: Flood Estimation Handbook, Willingford, UK, 1999.; Jain, S. and Lall, U.: Magnitude and timing of annual maximum floods: Trends and large-scale climatic associations for the Blacksmith Fork river, Utah, Water Resour. Res., 36, 3641–3651, 2000.; Jain, S. and Lall, U.: Floods in a changing climate: Does the past represent the future?, Water Resour. Res., 37, 3193–3205, 2001.


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