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Anthony Christopher Davison

Publications associées (80)

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Comment: Models Are Approximations!

Anthony Christopher Davison, Erwan Fabrice Koch, Jonathan Koh Boon Han

This discussion focuses on areas of disagreement with the papers, particularly the target of inference and the case for using the robust 'sandwich' variance estimator in the presence of moderate mis-specification. We also suggest that existing procedures m ...

INST MATHEMATICAL STATISTICS2019

Optimal regionalization of extreme value distributions for flood estimation

Anthony Christopher Davison, Sebastian Engelke, Peiman Asadi

Regionalization methods have long been used to estimate high return levels of river discharges at ungauged locations on a river network. In these methods, discharge measurements from a homogeneous group of similar, gauged, stations are used to estimate hig ...

2018

High-dimensional peaks-over-threshold inference

Anthony Christopher Davison, Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville

Max-stable processes are increasingly widely used for modelling complex extreme events, but existing fitting methods are computationally demanding, limiting applications to a few dozen variables. r-Pareto processes are mathematically simpler and have the p ...

2018

Dependence properties of spatial rainfall extremes and areal reduction factors

Anthony Christopher Davison, Sebastian Engelke

Areal reduction factors (ARFs) transform an estimate of extreme rainfall at a point to an estimate of extreme rainfall over a spatial domain, and are commonly used in flood risk estimation. For applications such as the design of large infrastructure, dam s ...

2018

Efficient inference for genetic association studies with multiple outcomes

Anthony Christopher Davison, Jörg Hager, Hélène Ruffieux

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on ma ...

Oxford University Press2017

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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-Blackwell2017

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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 Verlag2016

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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 Verlag2016

Likelihood 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 ...

Springer2016

Bayesian Inference For The Brown-Resnick Process, With An Application To Extreme Low Temperatures

Anthony Christopher Davison, Emeric Rolland Georges Thibaud

The Brown-Resnick max-stable process has proven to be well suited for modeling extremes of complex environmental processes, but in many applications its likelihood function is intractable and inference must be based on a composite likelihood, thereby preve ...

Inst Mathematical Statistics2016