Variable selection in infinite-dimensional problems

By Germán Aneiros, Philippe Vieu. 2014

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Interval-wise testing for functional data (2017, methodology): “Ferraty, Hall, and Vieu 2010; Aneiros and Vieu 2014, 2015, 2016; Berrendero, Cuevas, and Torrecilla 2016b). In some cases, special attention is drawn to perform the impact-point selection while eliminating redundant information provided by highly correlated points of the domain (e.g. Berrendero, Cue”
Selection of time instants and intervals with Support Vector Regression for multivariate functional data (2020, methodology): “sugar The goal of data set sugar, from Aneiros and Vieu (2014), is to predict the percentage of ash content from the fluorescence spectra, measured on 266 samples of sugar. sunflower The sunflower database comes from Picheny et al. (2019) and can be obtained in https://github.”
Selected statistical methods of data analysis for multivariate functional data (2018, methodology): “This is at the center of variable selection methods in functional data analysis (Aneiros and Vieu 2014).”
On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification (2015, methodology): “This approach is well established in functional regression where a wide range of VS methodologies, mostly dealing with penalized linear models, have been proposed (Aneiros and Vieu, 2014). In the functional supervised classification setting, the specific nature of this problem has motivated differen”