Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Valdora, Marina"'
Autor:
Valdora, Marina, Agostinelli, Claudio
Robust estimators for Generalized Linear Models (GLMs) are not easy to develop because of the nature of the distributions involved. Recently, there has been an increasing interest in this topic, especially in the presence of a possibly large number o
Externí odkaz:
http://arxiv.org/abs/2312.04661
Autor:
Boente, Graciela, Valdora, Marina
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 two populations. As in functional linear regression, regularization to
Externí odkaz:
http://arxiv.org/abs/2308.02786
During an epidemic outbreak of a new disease, the probability of dying once infected is considered an important though difficult task to be computed. Since it is very hard to know the true number of infected people, the focus is placed on estimating
Externí odkaz:
http://arxiv.org/abs/2109.03087
Autor:
Sued, Mariela, Valdora, Marina
Sampling distribution, a foundational concept in statistics, is difficult to understand, since we usually have only one realization of the estimator of interest. In this work, we present an innovative method for helping university students understand
Externí odkaz:
http://arxiv.org/abs/2105.02727
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 outliers can have a large impact on this estimator. Robust procedures are
Externí odkaz:
http://arxiv.org/abs/1709.10261
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 the missing responses, a vector X of covariates is observed at each indi
Externí odkaz:
http://arxiv.org/abs/1707.01951
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 properties of IPW estimators, the propensity score is supposed to be boun
Externí odkaz:
http://arxiv.org/abs/1704.01978
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 maximum rank correlation estimator is used to consistently estimate the s
Externí odkaz:
http://arxiv.org/abs/1703.09626
Akademický článek
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Publikováno v:
In Computational Statistics and Data Analysis June 2019 134:144-156
