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For α ∈ (0, 1) an α−trimming, P ∗, of a probability P is a new probability obtained by re-weighting the probability of any Borel set, B, according to a positive weight function, f ≤ 1 1−α , in the way P ∗(B) = R B f(x)P (dx). If P,Q are probability measures on Euclidean space, we consider the problem of obtaining the best L2−Wasserstein approximation… (More)

- Pedro C. Álvarez-Esteban, Eustasio del Barrio, Juan Antonio Cuesta-Albertos, Carlos Matrán
- Computational Statistics & Data Analysis
- 2010

The use of trimming procedures constitutes a natural approach to robustifying statistical methods. This is the case of goodness-of-fit tests based on a distance, which can be modified by choosing trimmed versions of the distributions minimizing that distance. In this paper we consider the L2-Wasserstein distance and introduce the trimming methodology for… (More)

- Pedro C. Álvarez-Esteban, Eustasio del Barrio, Juan Antonio Cuesta-Albertos, Carlos Matrán
- Computational Statistics & Data Analysis
- 2013

We consider a k-sample problem, k > 2, where samples have been obtained from k (random) generators, and we are interested in identifying those samples, if any, that exhibit substantial deviations from a pattern given by most of the samples. This main pattern would consist of component samples which should exhibit some internal degree of similarity. To… (More)

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