2 citations · 4 across the 8 of their papers we have counts for
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Robust Estimation in High Dimensional Generalized Linear Models
Marina Valdora, Claudio Agostinelli, Victor J. Yohai
Generalized Linear Models are routinely used in data analysis. The classical procedures for estimation are based on Maximum Likelihood and it is well known that the presence of out…
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…
Models for the Propensity Score that Contemplate the Positivity Assumption and their Application to Missing Data and Causality
Julieta Molina, Mariela Sued, Marina Valdora
Generalized linear models are often assumed to fit propensity scores, which are used to compute inverse probability weighted (IPW) estimators. In order to derive the asymptotic pro…
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…