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20172026
most citedRobust Doubly Protected Estimators for Quantiles with Missing Data

2 citations · 4 across the 5 of their papers we have counts for

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stat.ME2026

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…

stat.ME2023

Robust Penalized Estimators for High--Dimensional Generalized Linear Models

Marina Valdora, Claudio Agostinelli

Robust estimators for generalized linear models (GLMs) are not easy to develop due to the nature of the distributions involved. Recently, there has been growing interest in robust…

stat.ME2023

Robust estimation for functional logistic regression models

Graciela Boente, Marina Valdora

This paper addresses the problem of providing robust estimators under a functional logistic regression model. Logistic regression is a popular tool in classification problems with…

stat.ME20172 cited

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…

stat.ME20171 cited

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…