We review some fundamentals of extreme value theory which concern the stochastic behavior of the extreme values in a single process. We illustrate the power of the theory by means of four applications to climate data from different parts of the world: rainfall data from Florida, wind data from New Zealand, rainfall data from South Korea and flood data from Taiwan.
Maria Ivette Gomes, Armelle Guillou. Extreme Value Theory and Statistics of Univariate Extremes: A Review. International Statistical Review, Wiley, 2015, 83 (2),
REVSTAT – Statistical Journal, Vol. 6, No. 1, 2008, 83–100 The aim of this paper is to give a brief overview about several tests published in the context of statistical choice of extreme value domains and for assessing extreme value conditions. Some of the most recent testing procedures encompassed in this framework will be illustrated using a teletraffic data set.
Journal of Banking & Finance 24 (2000) 1097±1130
We consider the full statistical families of extreme value distributions $$G_{\beta ,\sigma ,\mu } $$ and generalized Pareto distributions $$H_{\beta ,\sigma ,\mu } $$ , where $$\beta \in \mathbb
Extreme value distributions - Gumbel, Frechet, Weibull, and GEV models: theory, applications, and software tools
In this paper, Extreme Value Theory (EVT) is presented to analyze wireless network traffic. The role of EVT is to allow the development of procedures that are scientifically and statistically rational
In this research statistic analyses of Web traffic were carried out based on Empirical Distribution Function (EDF) test. Several probability distributions, such as Pareto (simple), extreme value, Weibull (three parameters), exponential, logistic, Pareto (generalized) have been chosen to fit the experimental traffic data (traces) which how an analytical indication of traffic behaviour.
Extreme value theory has emerged as one of the most important statistical disciplines for the applied sciences for traffic prediction in telecommunications. Here we do some basic data analysis in extreme value analysis.
A Review of Probabilistic Methods of Assessment of Load Effects in Bridges