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Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

机译:基于Monte Carlo仿真的非间断广义物流模型的比较

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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.
机译:最近,在降雨和流量数据等水文数据中观察到气候变化的证据。水文数据中的统计数据的时间依赖性特征被广泛定义为非间转性。因此,已经提出了各种非营养性GEV和广义帕累托模型,分别用于频率分析,分别用于频率分析(峰值过度阈值)数据。然而,由于基于气候变化的非间平数据的复杂特性分析,因此不含替代模型。本研究提出了包括时间依赖参数的非间平广义逻辑模型。使用基于牛顿 - 拉文申方法的最大似然方法估计所提出的模型的参数。此外,所提出的模型由蒙特卡罗模拟进行比较,以研究模型和适用性的特性。

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