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most citedFast unfolding of communities in large networks

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12 papers · 1 filter

math.ST20093 cited

Nonparametric estimation of an extreme-value copula in arbitrary dimensions

Gordon Gudendorf, Johan Segers

Inference on an extreme-value copula usually proceeds via its Pickands dependence function, which is a convex function on the unit simplex satisfying certain inequality constraints…

math.ST200919 cited

Nonparametric "regression" when errors are positioned at end-points

Peter Hall, Ingrid Van Keilegom

Increasing practical interest has been shown in regression problems where the errors, or disturbances, are centred in a way that reflects particular characteristics of the mechanis…

math.ST2009231 cited

Extending the scope of empirical likelihood

Nils Lid Hjort, Ian W. McKeague, Ingrid Van Keilegom

This article extends the scope of empirical likelihood methodology in three directions: to allow for plug-in estimates of nuisance parameters in estimating equations, slower than $…

math.ST20091 cited

Second-order refined peaks-over-threshold modelling for heavy-tailed distributions

Jan Beirlant, Elisabeth Joossens, Johan Segers

Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD) is the most popular approach in extreme value statistics. This method typicall…

math.ST2008

A Sliding Blocks Estimator for the Extremal Index

Christian Y. Robert, Johan Segers, Christopher A. T. Ferro

In extreme value statistics for stationary sequences, blocks estimators are usually constructed by using disjoint blocks because exceedances over high thresholds of different block…

math.ST200859 cited

Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribution

John H. J. Einmahl, Johan Segers

Consider a random sample from a bivariate distribution function in the max-domain of attraction of an extreme-value distribution function . This is characterized by two…