95 citations · 192 across the 22 of their papers we have counts for
7 papers · 1 filter
Threshold detection under a semiparametric regression model
Graciela Boente, Florencia Leonardi, Daniela Rodriguez +1
Linear regression models have been extensively considered in the literature. However, in some practical applications they may not be appropriate all over the range of the covariate…
Asymptotic behaviour of penalized robust estimators in logistic regression when dimension increases
Ana M. Bianco, Graciela Boente, Gonzalo Chebi
Penalized estimators for logistic regression models have been previously study for fixed dimension in order to obtain sparse statistical models and automatic variable selection…
Robust smoothed canonical correlation analysis for functional data
Graciela Boente, Nadia Kudraszow
This paper provides robust estimators for the first canonical correlation and directions of random elements on Hilbert separable spaces by using robust association and scale measur…
The spatial sign covariance operator: Asymptotic results and applications
Graciela Boente, Daniela Rodriguez, Mariela Sued
Due to the increasing recording capability, functional data analysis has become an important research topic. For functional data the study of outlier detection and/or the developme…
Robust estimators in a generalized partly linear regression model under monotony constraints
Graciela Boente, Daniela Rodriguez, Pablo Vena
In this paper, we consider the situation in which the observations follow an isotonic generalized partly linear model. Under this model, the mean of the responses is modelled, thro…
Testing equality between several populations covariance operators
Graciela Boente, Daniela Rodriguez, Mariela Sued
In many situations, when dealing with several populations, equality of the covariance operators is assumed. An important issue is to study if this assumption holds before making ot…
Robust functional principal components: A projection-pursuit approach
Juan Lucas Bali, Graciela Boente, David E. Tyler +1
In many situations, data are recorded over a period of time and may be regarded as realizations of a stochastic process. In this paper, robust estimators for the principal componen…