Results 11 to 20 of about 67,239 (298)
evgam: An R Package for Generalized Additive Extreme Value Models [PDF]
Journal of Statistical Software, 2022 This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions.
Benjamin D. Youngman
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Probability Statistical Model for Measured Ground Motion Based on Generalized Extreme Value Distribution [PDF]
Shanghai Jiaotong Daxue xuebaoTo develop a probability distribution model of peak ground acceleration, 255365 ground motion recordings are collected from 500 stations to create initial statistical samples of peak ground acceleration.
FENG Pengfei, ZHOU Mi, LI Zhixuan, ZHU Guoqiang
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Asymptotic posterior normality of the generalized extreme value distribution [PDF]
, 2021 The univariate generalized extreme value (GEV) distribution is the most commonly used tool for analyzing the properties of rare events. The ever greater utilization of Bayesian methods for extreme value analysis warrants detailed theoretical investigation, which has thus far been underdeveloped.
Zhang, Likun, Shaby, Benjamin A.
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On the maximum likelihood estimator for the Generalized Extreme-Value distribution [PDF]
Extremes, 2017 The vanilla method in univariate extreme-value theory consists of fitting the three-parameter Generalized Extreme-Value (GEV) distribution to a sample of block maxima. Despite claims to the contrary, the asymptotic normality of the maximum likelihood estimator has never been established.
Buecher, Axel, Segers, Johan
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e-GFOS, 2021 The aim of this work is to improve a method for determining the characteristic values of climatic loads according to a probabilistic model of the annual maxima sequence, by choosing a rational type of generalized extreme value distribution law.
Mykola Pashynskyi +2 more
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Prediction of extreme rainfall with a generalized extreme value distribution [PDF]
Journal of the Korean Data and Information Science Society, 2013 Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to ...
Yong Kyu Sung, Joong K. Sohn
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GENERALIZED EXTREME VALUE DISTRIBUTION PARAMETERS AS DYNAMICAL INDICATORS OF STABILITY [PDF]
International Journal of Bifurcation and Chaos, 2012 We introduce a new dynamical indicator of stability based on the Extreme Value statistics showing that it provides an insight into the local stability properties of dynamical systems. The indicator performs faster than others based on the iteration of the tangent map since it requires only the evolution of the original systems and, in the chaotic ...
Davide Faranda +3 more
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Reliability of Extreme Wind Speeds Predicted by Extreme-Value Analysis
Meteorology, 2023 The reliability of extreme wind speed predictions at large mean recurrence intervals (MRI) is assessed by bootstrapping samples from representative known distributions.
Nicholas John Cook
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Bootstrapping Time-Varying Uncertainty Intervals for Extreme Daily Return Periods
International Journal of Financial Studies, 2022 This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data.
Katleho Makatjane, Tshepiso Tsoku
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The Topp-Leone generalized extreme value distribution: Extreme value analysis and return level estimation of the PM2.5 in Chiang Mai, Thailand [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2022 In this paper, an extension of the generalized extreme value (GEV) distribution called the Topp Leone-GEV (TL-GEV) distribution is applied. The TL-GEV distribution has four parameters (λ, μ, σ, ξ), and it has the three named sub-models TLGumbel (for ξ =
Sirinapa Aryuyuen, Winai Bodhisuwan
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