DI BERNARDINO , Elena

In the present article we study the average of Lipschitz-Killing (LK) curvatures of the excursion set of a stationary isotropic Gaussian field X on R 2. The novelty is that the field can be nonstandard, that is, with unknown mean and variance, which is more realistic from an applied viewpoint. To cope with the unknown location and scale...

In this paper we study some statistics linked to the average of Lipschitz-Killing (LK) curvatures of the excursion set of a stationary non-standard isotropic Gaussian field X on R 2. Under this hypothesis of unknown location and scale parameters of X, we introduce novel fundamental quantities, that we call effective level and effective spectral...

The classic univariate risk measure in environmental sciences is the Return Period (RP). The RP is traditionally defined as "the average time elapsing between two successive realizations of a prescribed event". The notion of design quantile related with RP is also of great importance. The design quantile represents the "value of the variable(s)...

Let Ti:=[Xi|X∈∂L(α)], for i = 1,…,d, where X = (X1,…,Xd) is a risk vector and ∂L(α) is the associated multivariate critical layer at level α∈(0,1). The aim of this work is to propose a non-parametric extreme estimation procedure for the (1 − pn)-quantile of Ti for a fixed α and when pn→0, as the sample size n→+∞. An extrapolation method is...

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In this paper we consider digital images for which the pixels values are given by a sequence of independent and identically distributed variables within an observation window. We proceed to the construction of an unbiased estimator for the perimeter without border effects. The study of the first and second moments of the perimeter allows to...

In this paper we consider digital images for which the pixels values are given by a sequence of independent and identically distributed variables within an observation window. We proceed to the construction of an unbiased estimator for the perimeter without border effects. The study of the first and second moments of the perimeter allows to...

In this paper we consider digital images for which the pixels values are given by a sequence of independent and identically distributed variables within an observation window. We proceed to the construction of an unbiased estimator for the perimeter without border effects. The study of the first and second moments of the perimeter allows to...

This paper focuses on semi-parametric estimation of multivariate expectiles for extreme levels of risk. Multivariate expectiles and their extremes have been the focus of plentiful research in recent years. In particular, it has been noted that due to the difficulty in estimating these values for elevated levels of risk, an alternative...

Erratum to: Metrika DOI 10.1007/s00184-014-0498-4

The aim of this paper is to study the behavior of a covariate func-tion in a multivariate risks scenario. The first part of this paper deals with the problem of estimating the c-upper level sets L(c) = {F (x) ≥ c}, with c ∈ (0, 1), of an unknown distribution function F on R d + . A plug-in approach is followed. We state consistency results with...

Forest fires burn an average of about 440 000 ha each year in southern Europe. These fires cause numerous casualties and deaths and destroy houses and other infrastructure. In order to elaborate on suitable firefighting strategies, complex interactions between human and environmental factors must be taken into account. In this study, we...

We are interested in creating statistical methods to provide informative summaries of random fields through the geometry of their excursion sets.To this end, we introduce an estimator for the length of the perimeter of excursion sets of random fields on $\mathbb R^2$ observed over regular square tilings. The proposed estimator acts on the...

We are interested in creating statistical methods to provide informative summaries of random fields through the geometry of their excursion sets. To this end, we introduce an estimator for the length of the perimeter of excursion sets of random fields on observed over regular square tilings. The proposed estimator acts on the empirically...

We introduce the extremal range, a local statistic for studying the spatial extent of extreme events in random fields on $\mathbb{R}^d$. Conditioned on exceedance of a high threshold at a location s, the extremal range at $s$ is the random variable defined as the smallest distance from $s\in\mathbb{R}^d$ to a location where there is a...

This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in central eastern Canada. Furthermore, we provide a comparison with different classical interpolation-based approaches. The considered data represents a station network particularly spatially sparse. Furthermore, one observes...

This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in central eastern Canada. Furthermore, we provide a comparison with different classical interpolation-based approaches. The considered data represents a station network particularly spatially sparse. Furthermore, one observes...

This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in Central Eastern Canada. The considered data contains a large portion of missing values, and one observes several nonconcomitant record periods at different stations. The proposed two-step approach combines GEV parameters'...

In the present paper we study three geometrical characteristics for the excursion sets of a two-dimensional stationary isotropic random field. First, we show that these characteristics can be estimated without bias if the considered field satisfies a kinematic formula, this is for instance the case of fields given by a function of smooth...

Modéliser la dépendance entre maxima est un sujet d'intérêt dans les domaines d'application d'analyse du risque. Dans cet objectif, la copule de valeurs extrêmes, caractérisée par le madogramme, peut être utilisée comme une description de la structure de dépendance. Concrètement, la famille des distributions à valeurs extrêmes est très riche...

The dependence structure between extreme observations can be complex. For that purpose, we see clustering as a tool for learning the complexextremal dependence structure. We introduce the Asymptotic Independent block (AI-block) model, a model-based clustering where population-level clusters are clearly defined using independence of clusters'...

This paper deals with the problem of estimating the level sets of an unknown distribution function $F$. A plug-in approach is followed. That is, given a consistent estimator $F_n$ of $F$, we estimate the level sets of $F$ by the level sets of $F_n$. In our setting no compactness property is a priori required for the level sets to estimate. We...