Which Extreme Values Are Really Extreme? [PDF]
, 2004 We define the extreme values of any random sample of size n from a distribution function F as the observations exceeding a threshold and following a type of generalized Pareto distribution (GPD) involving the tail index of F.
Gonzalo, Jesús +4 more
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Statistical modeling of maximum temperature in Guinea [PDF]
Anais da Academia Brasileira de CiênciasA statistical analysis of maximum temperature from twelve weather stations in parts of Guinea is provided. Using maximum likelihood estimation, maximum temperature data was fitted by the Generalized Extreme Value distribution. Data from all of the twelve
MALICK KEBE, SARALEES NADARAJAH
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Spatial Patterns in the Extreme Dependence of Ozone Pollution between Cities in China’s BTH Region
Atmosphere, 2023 Ozone pollution in China has become increasingly severe in recent years. Considering the damage that extreme ozone pollution may cause and the fact that the occurrence of extreme ozone pollution among different locations may be related, this paper uses ...
Lu Deng, Siqi Sheng
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Statistical Modelling of Extreme Data of Air Pollution in Pekanbaru City
InPrime, 2019 Air pollution is a phenomenon that is often discussed, especially regarding air quality in urban areas. This has become a major contributor to health problems and environmental issues in Asian countries, such as Indonesia, especially Riau Province.
Ari Pani Desvina +2 more
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Minimum Sample Size Determination for Generalized Extreme Value Distribution
Communications in Statistics - Simulation and Computation, 2010 Sample size determination is an important issue in statistical analysis. Obviously, the larger the sample size is, the better the statistical results we have. However, in many areas such as coastal engineering and environmental sciences, it can be very expensive or even impossible to collect large samples. In this paper, we propose a general method for
Yuzhi Cai, Dominic Hames
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Bayesian modeling of dynamic extreme values: extension of generalized extreme value distributions with latent stochastic processes [PDF]
Journal of Applied Statistics, 2016 ABSTRACTThis paper develops Bayesian inference of extreme value models with a flexible time-dependent latent structure. The generalized extreme value distribution is utilized to incorporate state variables that follow an autoregressive moving average (ARMA) process with Gumbel-distributed innovations.
Jouchi Nakajima +2 more
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Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia [PDF]
Proceedings of the International Association of Hydrological Sciences, 2014 Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events.
F. Alahmadi +4 more
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Reference Priors for the Generalized Extreme Value Distribution
Statistica SinicaSummary: We derive a collection of reference prior distributions for a Bayesian analysis under the three-parameter generalized extreme value (GEV) distribution. These priors are based on an established formal definition of oninformativeness. They depend on the ordering of the three parameters, and we show that the GEV is unusual in that some orderings ...
Zhang, Likun, Shaby, Benjamin A
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Flood Frequency Analyses over Different Basin Scales in the Blue Nile River Basin, Ethiopia
Hydrology, 2020 The frequency and intensity of flood quantiles and its attendant damage in agricultural establishments have generated a lot of issues in Ethiopia. Moreover, precise estimates of flood quantiles are needed for efficient design of hydraulic structures ...
Getachew Tegegne +3 more
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A regression method of estimation for generalized extreme value distribution [PDF]
Kybernetikasummary:This study focuses on parameter estimation for the generalized extreme value distribution (GEVD) using the regression method described by [Van2012median].
R. Anand, C. Chandran
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