Anthony Christopher Davison

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We investigate the entrainment, deposition and motion of coarse spherical particles within a turbulent shallow water stream down a steep slope. This is an idealization of bed-load transport in mountain streams. Earlier investigations have described this ki ...

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 ...

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, ...

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 ...

We discuss the use of likelihood asymptotics for inference on risk measures in univariate extreme value problems, focusing on estimation of high quantiles and similar summaries of risk for uncertainty quantification. We study whether higher-order approxima ...

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 ...

Accurately quantifying extreme rainfall is important for the design of hydraulic structures, for flood mapping and zoning and for disaster management. In order to produce maps of estimates of 25-year rainfall return levels in Brazil, we selected 893 shorte ...

We present the first spatial analysis of "fingerprints" of the El Nino/Southern Oscillation (ENSO) and atmospheric aerosol load after major volcanic eruptions (El Chichon and Mt. Pinatubo) in extreme low and high (termed ELOs and EHOs, respectively) and me ...

Confounding variables are a recurrent challenge for causal discovery and inference. In many situations, complex causal mechanisms only manifest themselves in extreme events, or take simpler forms in the extremes. Stimulated by data on extreme river flows a ...

Classical peaks over threshold analysis is widely used for statistical modeling of sample extremes, and can be supplemented by a model for the sizes of clusters of exceedances. Under mild conditions a compound Poisson process model allows the estimation of ...

Max-stable processes are the natural analogues of the generalized extreme-value distribution when modelling extreme events in space and time. Under suitable conditions, these processes are asymptotically justified models for maxima of independent replicati ...

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 ...

Over the last quarter-century, spacecraft conjunction assessment has focused on a quantity associated by its advocates with collision probability. This has a well-known dilution feature, whereby it is small when uncertainty is large, that may give false confidence that a conjunction is safe when it is not. An alternative approach to conjunction assessment is to assess the missed detection probability that the best available information indicates the conjunction to be safe, when it is actually unsafe. In oth

In this study the frequency of days with extreme low (termed ELOs) and extreme high (termed EHOs) total ozone values and their influence on mean values and trends are analyzed for the world's longest total ozone record (Arosa, Switzerland). The results sho ...

We consider inference on a vector-valued parameter of interest in a linear exponential family, in the presence of a finite-dimensional nuisance parameter. Based on higher-order asymptotic theory for likelihood, we propose a directional test whose p-value i ...

Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although some frequentist properties of the maximum composite likelihood estimator are akin to those of the maximu ...

Permafrost consists of soil and rocks that remain at 0 degrees C or below for at least two consecutive years. In mountains, permafrost ground ice acts like cement, stabilizing rock walls. Its degradation, following climate warming, may lead to slope instab ...

The need to model rare events of univariate time series has led to many recent advances in theory and methods. In this paper, we review telegraphically the literature on extremes of dependent time series and list some remaining challenges. ...

The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications. Mixtures of Dirichlet distributions have been proposed for use as a semiparametric model, but fitting them is awkward. In this article, we propose a new approach to the use

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 ...

Anthony Christopher Davison

Chattez avec Graph Search

Entrainment and motion of coarse particles in a shallow water stream down a steep slope

Fast Automatic Smoothing for Generalized Additive Models

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

Dependence properties of spatial rainfall extremes and areal reduction factors

Improved Inference On Risk Measures For Univariate Extremes

Human mortality at extreme age

Practical issues with modeling extreme Brazilian rainfall

On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes - Part 2: The effects of the El Nino/Southern Oscillation, volcanic eruptions and contributions of atmospheric dynamics and chemistry to long-term total ozone changes

Causal modelling of heavy-tailed variables and confounders with application to river flow

Model misspecification in peaks over threshold analysis

Space-time modelling of extreme events

Efficient inference for genetic association studies with multiple outcomes

Inference on the Miss Distance in a Conjunction

Extreme events in total ozone over Arosa---Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes

Accurate Directional Inference for Vector Parameters in Linear Exponential Families

Bayesian inference from composite likelihoods, with an application to spatial extremes

Statistical modelling of ground temperature in mountain permafrost

Modelling Time Series Extremes

Bayesian clustering of multivariate extremes

Likelihood estimators for multivariate extremes