Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

S. Kim, W. Nam, H. Ahn, T. Kim, Jun-Haeng Heo

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

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 nonstation-arity. 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.

Original languageEnglish
Pages (from-to)65-68
Number of pages4
JournalIAHS-AISH Proceedings and Reports
Volume371
DOIs
Publication statusPublished - 2015 Jan 1
EventHS02 � Hydrologic Non-Stationarity and Extrapolating Models to Predict the Future in the 2015 IUGG General Assembly - Prague, Czech Republic
Duration: 2015 Jun 222015 Jul 2

Fingerprint

logistics
simulation
frequency analysis
climate change
comparison
rainfall
method
parameter

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Cite this

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title = "Comparison of nonstationary generalized logistic models based on Monte Carlo simulation",
abstract = "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 nonstation-arity. 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.",
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Comparison of nonstationary generalized logistic models based on Monte Carlo simulation. / Kim, S.; Nam, W.; Ahn, H.; Kim, T.; Heo, Jun-Haeng.

In: IAHS-AISH Proceedings and Reports, Vol. 371, 01.01.2015, p. 65-68.

Research output: Contribution to journalConference article

TY - JOUR

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AU - Nam, W.

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AB - 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 nonstation-arity. 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.

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