Robust weighted likelihood estimators with an application to bivariate extreme value problems

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Modelling Time Series Extremes (2012, methodology): “One way to deal with this is through robust estimation (Dupuis & Field, 1998; Dupuis & Morgenthaler, 2002; Dupuis, 2005), but another is through a penalty function corresponding to a prior.”
A robust prediction error criterion for pareto modelling of upper tails (2005, methodology): “We propose to implement the weighted maximum likelihood approach of Dupuis & Morgenthaler (2002).”
Extreme-value copulas (2009, background): “A robustiﬁed version of the maximum likelihood estimator is introduced in [20].”
Statistics of Extremes (2004, methodology): “Robust estimation within the bivariate logistic model is considered in Dupuis and Morgenthaler (2002). In the special case α = 1, corresponding to independence, the estimation problem is non-regular because of two reasons: the parameter is on the boundary of the parameter space, and the variance of ”