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Sub‐asymptotic motivation for new conditional multivariate extreme models

Publications associées (44)

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Statistical Inference for Partially Observed Stochastic Epidemics

Andrea Kraus

This work is concerned with the estimation of the spreading potential of the disease in the initial stages of an epidemic. A speedy and accurate estimation is important for determining whether or not interventions are necessary to prevent a major outbreak. ...

EPFL2013

Tuning the length dispersion of multi-walled carbon nanotubes by ball milling

László Forró, Arnaud Magrez, Claudio Grimaldi, Richard Gaal, Marijana Mionic Ebersold, Rita Smajda, Primoz Rebernik Ribic

The statistical analysis of the length distribution of catalytic chemical vapour deposition synthesized multi-walled carbon nanotubes cut by planetary ball milling is reported. The nanotube lengths follow a log-normal distribution in a broad range of grind ...

Amer Inst Physics2013

Are there "dragon-kings" events (i.e. genuine outliers) among extreme avalanches?

Christophe Ancey

Predicting the occurrence and spatial extent of extreme avalanches is a longstanding issue. Using field data pooled from various sites within the same mountain range, authors showed that the avalanche size distribution can be described using either an extr ...

Springer-Verlag2012

Bivariate Extreme Statistics, Ii

We review the current state of statistical modeling of asymptotically independent data. Our discussion includes necessary and sufficient conditions for asymptotic independence, results on the asymptotic independence of statistics of interest, estimation an ...

2012

A quantitative central limit theorem for the random walk among random conductances

Jean-Christophe Mourrat

We consider the random walk among random conductances on Z(d). We assume that the conductances are independent, identically distributed and uniformly bounded away from 0 and infinity. We obtain a quantitative version of the central limit theorem for this r ...

Univ Washington, Dept Mathematics2012

Stratégies de compromis pour l'estimation des paramètres de régression et pour la classification floue

Nicolas Fournier

Model specification is an integral part of any statistical inference problem. Several model selection techniques have been developed in order to determine which model is the best one among a list of possible candidates. Another way to deal with this questi ...

EPFL2011

Overcoming the limitations of traditional model-updating approaches

Ian Smith, James-Alexandre Goulet

Model updating is useful for improving structural performance assessments. This paper examines an important assumption of traditional model-updating approaches. This assumption requires the error independence between points where predictions and measuremen ...

ASCE2011

Statistical modeling of inter-device correlations with BPV

Ivica Stevanovic, Xuan Li

The backward propagation of variance (BPV) technique for statistical modeling has proven to be efficient and effective in practice. In this paper we extend the BPV formalism to explicitly include modeling of the correlations between electrical performances ...

Elsevier2010

Likelihood-Based Inference for Max-Stable Processes

Simone Padoan

The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes However, their application is complicated due to the unavailability of the multivariate density function and so likehhood-based methods r ...

American Statistical Association2010

Statistical analysis of clusters of extreme events

Mária Süveges

The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...

EPFL2009