188 citations · 322 across the 17 of their papers we have counts for
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Optimal robust estimators for families of distributions on the integers
Ricardo A. Maronna, Victor J. Yohai
Let F_{θ} be a family of distributions with support on the set of nonnegative integers Z_0. In this paper we derive the M-estimators with smallest gross error sensitivity (GES). We…
Multivariate Location and Scatter Matrix Estimation Under Cellwise and Casewise Contamination
Andy Leung, Victor J. Yohai, Ruben H. Zamar
We consider the problem of multivariate location and scatter matrix estimation when the data contain cellwise and casewise outliers. Agostinelli et al. (2015) propose a two-step ap…
Robust and sparse estimators for linear regression models
Ezequiel Smucler, Víctor J. Yohai
Penalized regression estimators are a popular tool for the analysis of sparse and high-dimensional data sets. However, penalized regression estimators defined using an unbounded lo…
Robust and efficient estimation of high dimensional scatter and location
Ricardo A. Maronna, Victor J. Yohai
We deal with the equivariant estimation of scatter and location for p-dimensional data, giving emphasis to scatter. It it important that the estimators possess both a high efficien…
Composite Robust Estimators for Linear Mixed Models
Claudio Agostinelli, Victor J. Yohai
The Classical Tukey-Huber Contamination Model (CCM) is a usual framework to describe the mechanism of outliers generation in robust statistics. In a data set with observations…
Dynamic Principal Components in the Time Domain
Daniel Peña, Víctor J. Yohai
We propose a time domain approach to define dynamic principal components (DPC) using a reconstruction of the original series criterion. This approach to define DPC was introduced b…