Most-predictive design points for functional data predictors

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Functional Data Analysis (2016, background): “…i.e., regression models with time-based rather than frequency-based predictors, can be viewed as special cases of the continuously additive model (24), where only a few time points and their associated additive functions f j ( X ( t j )) are assumed to be predictive (Ferraty, Hall & Vieu 2010).”
On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification (2015, methodology): “Variable selection (VS) is becoming a popular methodology for dimension reduction in FDA, alongside with the classical Principal Component Analysis (PCA, see Hall, P. (2011) for a survey) or Partial Least Squares (PLS, see Delaigle and Hall (2012b)).”
Componentwise classification and clustering of functional data (2012, methodology): “This is the approach taken by Ferraty et al. (2010) in a related problem of functional prediction.”
Selection of time instants and intervals with Support Vector Regression for multivariate functional data (2020, methodology): “Observe that our proposed heuristic differs from a greedy approach (Berrendero et al., 2019; Ferraty et al., 2010), since our proposal utilizes the optimal solution of level h as a starting solu-tion of the level h þ 1, allowing a very different solution for level h þ 1 than the one obtained in the…”