Asymptotically distribution-free goodness-of-fit testing for tail copulas [PDF]
, 2014 Let $(X_1,Y_1),\ldots,(X_n,Y_n)$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution.
Can, Sami Umut +3 more
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Statistical Modeling of Spatial Extremes [PDF]
, 2012 The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection.
Davison, A. C. +2 more
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Likelihood estimators for multivariate extremes [PDF]
, 2015 The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high
Davison, Anthony C. +2 more
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Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks [PDF]
, 2009 Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to
Chernozhukov, Victor +1 more
core +3 more sources
Increasing power for voxel-wise genome-wide association studies : the random field theory, least square kernel machines and fast permutation procedures [PDF]
, 2012 Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics
Feng, Jianfeng +4 more
core +1 more source
, 2020 Markov chain Monte Carlo is a key computational tool in Bayesian statistics, but it can be challenging to monitor the convergence of an iterative stochastic algorithm.
Bürkner, Paul-Christian +4 more
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Divergence based Robust Estimation of the Tail Index through An Exponential Regression Model
, 2016 The extreme value theory is very popular in applied sciences including Finance, economics, hydrology and many other disciplines. In univariate extreme value theory, we model the data by a suitable distribution from the general max-domain of attraction ...
Ghosh, Abhik
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Extreme Value Statistics of the Total Energy in an Intermediate Complexity Model of the Mid-latitude Atmospheric Jet. Part I: Stationary case [PDF]
, 2006 A baroclinic model for the atmospheric jet at middle-latitudes is used as a stochastic generator of time series of the total energy of the system. Statistical inference of extreme values is applied to yearly maxima sequences of the time series, in the ...
Allen +43 more
core +4 more sources
On the Hill estimator: a comparison of methods [PDF]
, 2015 Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a
Ferreira, Marta Susana +1 more
core
Extreme Value Laws for Superstatistics
, 2014 We study the extreme value distribution of stochastic processes modeled by superstatistics. Classical extreme value theory asserts that (under mild asymptotic independence assumptions) only three possible limit distributions are possible, namely: Gumbel,
Beck, Christian, Rabassa, Pau
core +2 more sources