188 citations · 322 across the 17 of their papers we have counts for
8 papers · 1 filter
Robust estimation in generalized linear models based on the normal quantiles of the probability integral transformation
Marina Valdora, Víctor Yohai
A new approach to robust estimation in generalized linear models is introduced. The idea of the method is to first transform the responses applying the composition of the normal qu…
Forecasting High Dimensional Time Series with Dynamic Dimension Reduction
Daniel Peña, Victor J. Yohai
Many dimension reduction techniques have been developed for independent data, and most have also been extended to time series. However, these methods often fail to account for the…
Robust Model-Based Clustering
Juan D. Gonzalez, Ricardo Maronna, Victor J. Yohai +1
We propose a new class of robust and Fisher-consistent estimators for mixture models. These estimators can be used to construct robust model-based clustering procedures. We study i…
Forecasting Multiple Time Series with One-Sided Dynamic Principal Components
Daniel Peña, Ezequiel Smucler, Victor J. Yohai
We define one-sided dynamic principal components (ODPC) for time series as linear combinations of the present and past values of the series that minimize the reconstruction mean sq…
Robust Doubly Protected Estimators for Quantiles with Missing Data
Julieta Molina, Mariela Sued, Marina Valdora +1
Doubly protected estimators are widely used for estimating the population mean of an outcome Y from a sample where the response is missing in some individuals. To compensate for th…
Robust estimators for generalized linear models with a dispersion parameter
Michael Amiguet, Alfio Marazzi, Marina Valdora +1
Highly robust and efficient estimators for the generalized linear model with a dispersion parameter are proposed. The estimators are based on three steps. In the first step the max…