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Causality in extremes of time series
Consider two stationary time series with heavy-tailed marginal distributions. We aim to detect whether they have a causal relation, that is, if a...
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Improved Convergence Rates of Normal Extremes
It is well known that the convergence of the normal extremes to the limiting Gumbel distribution is extremely slow, at the rate of...
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High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields
The conditional extremes framework allows for event-based stochastic modeling of dependent extremes, and has recently been extended to spatial and...
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Extremes for stationary regularly varying random fields over arbitrary index sets
We consider the clustering of extremes for stationary regularly varying random fields over arbitrary growing index sets. We study sufficient...
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Handling missing extremes in tail estimation
In some data sets, it may be the case that a portion of the extreme observations is missing. This might arise in cases where the extreme observations...
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Stochastic ordering in multivariate extremes
The article considers the multivariate stochastic orders of upper orthants, lower orthants and positive quadrant dependence (PQD) among simple...
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Extremes of Markov random fields on block graphs: Max-stable limits and structured Hüsler–Reiss distributions
We study the joint occurrence of large values of a Markov random field or undirected graphical model associated to a block graph. On such graphs,...
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Modeling spatial extremes using normal mean-variance mixtures
Classical models for multivariate or spatial extremes are mainly based upon the asymptotically justified max-stable or generalized Pareto processes....
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Spatial extremes and stochastic geometry for Gaussian-based peaks-over-threshold processes
Geometric properties of exceedance regions above a given quantile level provide meaningful theoretical and statistical characterizations for...
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A marginal modelling approach for predicting wildfire extremes across the contiguous United States
This paper details a methodology proposed for the EVA 2021 conference data challenge. The aim of this challenge was to predict the number and size of...
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Bayesian Latent Gaussian Models for High-Dimensional Spatial Extremes
In this chapter, we show how to efficiently model high-dimensional extreme peaks-over-threshold events over space in complex non-stationary settings,...
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Analysis of wildfires and their extremes via spatial quantile autoregressive model
In this paper we propose a procedure to estimate the distribution of wildfire frequency and severity using the wildfire data measured by month during...
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On the Asymptotic Behaviour of Extremes of Observations from a Tempered Stable Distribution
In this article, we obtain the limit distribution of the maxima and minima of independent observations from tempered stable and bilateral gamma...
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Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution
A new method is proposed for modelling the yearly maxima of sub-daily precipitation, with the aim of producing spatial maps of return level...
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Extremes of censored and uncensored lifetimes in survival data
We consider a random censoring model for survival analysis, allowing the possibility that only a proportion of individuals in the population are...
