Concept
Copula (probability theory)
Related publications (40)
Modelling across extremal dependence classes
Anthony Christopher Davison, Jonathan A. Tawn, Jennifer Lynne Wadsworth
Different dependence scenarios can arise in multivariate extremes, entailing careful selection of an appropriate class of models. In bivariate extremes, the variables are either asymptotically dependent or are asymptotically independent. Most available sta ...
Wiley-Blackwell2017Caching of Bivariate Gaussians with Non-Uniform Preference Probabilities
Michael Christoph Gastpar, Guillaume Jean Op 't Veld
Caching is technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. We study this method in a lossy source coding setting with Gaussian databases. A good caching strategy minimizes the data ...
2017Robust Bounds In Multivariate Extremes
Extreme value theory provides an asymptotically justified framework for estimation of exceedance probabilities in regions where few or no observations are available. For multivariate tail estimation, the strength of extremal dependence is crucial and it is ...
Institute of Mathematical Statistics2017Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures
Emeric Rolland Georges Thibaud, Raphaël Huser
Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian processes, which are asymptotically independent except in the case of perfect depen ...
Elsevier Sci Ltd2017Robust Growth-Optimal Portfolios
Daniel Kuhn, Napat Rujeerapaiboon, Wolfram Wiesemann
The growth-optimal portfolio is designed to have maximum expected log-return over the next rebalancing period. Thus, it can be computed with relative ease by solving a static optimization problem. The growth-optimal portfolio has sparked fascination among ...
Informs2016Likelihood estimators for multivariate extremes
Anthony Christopher Davison, Raphaël Huser
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 t ...
Springer2016Bayesian Uncertainty Management in Temporal Dependence of Extremes
Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn
Both marginal and dependence features must be described when modelling the extremes of a stationary time series. There are standard approaches to marginal modelling, but long- and short-range dependence of extremes may both appear. In applications, an assu ...
Springer Verlag2016Bayesian uncertainty management in temporal dependence of extremes
Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn
Both marginal and dependence features must be described when modelling the extremes of a stationary time series. There are standard approaches to marginal modelling, but long-and short-range dependence of extremes may both appear. In applications, an assum ...
Springer Verlag2016Dimensionality Reduction in Dynamic Optimization under Uncertainty
Dynamic optimization problems affected by uncertainty are ubiquitous in many application domains. Decision makers typically model the uncertainty through random variables governed by a probability distribution. If the distribution is precisely known, then ...
EPFL2016Sources and forms of modelling uncertainties for structural identification
The aim of model-based structural identification is to make sense of monitoring data in order to improve knowledge of the real behaviour of structures. Common use of structural-identification techniques involves an assumption of independent zero-mean Gauss ...
2015