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Anthony Christopher Davison

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Publications associées (93)

Human mortality at extreme age

Anthony Christopher Davison, Léo Raymond-Belzile

We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...

ROYAL SOC2021

A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma

Anthony Christopher Davison, Hélène Ruffieux, Radu Popescu, Jörg Hager

Molecular quantitative trait locus (QTL) analyses are increasingly popular to explore the genetic architecture of complex traits, but existing studies do not leverage shared regulatory patterns and suffer from a large multiplicity burden, which hampers the ...

PUBLIC LIBRARY SCIENCE2020

Discussion

Anthony Christopher Davison

AMER STATISTICAL ASSOC2020

The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management

Anthony Christopher Davison, Silvia Hostettler, Alfredo Rafael Kägi Trejo, Nicola Mary Banwell

Although disaster risk management is becoming increasingly important in development cooperation, there is still a lack of robust evidence regarding its effectiveness. Few studies based on a counterfactual have been conducted in the fields of disaster manag ...

2020

An unethical optimization principle

Anthony Christopher Davison

If an artificial intelligence aims to maximize risk-adjusted return, then under mild conditions it is disproportionately likely to pick an unethical strategy unless the objective function allows sufficiently for this risk. Even if the proportion eta of ava ...

ROYAL SOC2020

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Anthony Christopher Davison, Hélène Ruffieux, Jörg Hager

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...

INST MATHEMATICAL STATISTICS2020

Special Issue: "Data Science versus Classical Inference: Prediction, Estimation, and Attribution", honouring Prof. Brad Efron's International Prize in Statistics in 2019 Discussion

Anthony Christopher Davison

WILEY2020

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

Fast Automatic Smoothing for Generalized Additive Models

Anthony Christopher Davison, Yousra El Bachir

Generalized additive models (GAMs) are regression models wherein parameters of probability distributions depend on input variables through a sum of smooth functions, whose degrees of smoothness are selected by L-2 regularization. Such models have become th ...

Microtome Publishing2019

Overcoming Multi-model Forgetting

Anthony Christopher Davison, Mathieu Salzmann, Yassine Benyahia, Claudiu-Cristian Musat, Kaicheng Yu, Martin Jaggi

We identify a phenomenon, which we refer to as multi-model forgetting, that occurs when sequentially training multiple deep networks with partially-shared parameters; the performance of previously-trained models degrades as one optimizes a subsequent one, ...

JMLR2019

Optimal regionalization of extreme value distributions for flood estimation

Anthony Christopher Davison, Peiman Asadi, Sebastian Engelke

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

Automatic module selection from several microarray gene expression studies

Anthony Christopher Davison, Darlene Goldstein, Alix Corinne Josiane Colette Zollinger

2018

'The life of man, solitary, poore, nasty, brutish, and short': Discussion of the paper by Rootzen and Zholud

Anthony Christopher Davison

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

Modelling across extremal dependence classes

Anthony Christopher Davison, Jennifer Lynne Wadsworth, Jonathan A. Tawn

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

Efficient inference for genetic association studies with multiple outcomes

Anthony Christopher Davison, Hélène Ruffieux, Jörg Hager

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

Bayesian 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 Verlag2016

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

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

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