affect classification. We focus on the form of ℓ1 penalties in logistic regression models for functional data, in particular …

developed. When the functional data lie on an unknown intrinsically low-dimensional smooth manifold, the corresponding empirical …

problems. The purpose of this work is to present some new insights in the context of nonparametric inference on functional data …The permutation approach for testing the equality of distributions and thereby comparing two populations of functional … data has recently received increasing attention thanks to the flexibility of permutation tests to handle complex testing …

assumes periodicity in its autocorrelation function. Plausibly, it explains spatial functional data resulted from phenomena …

Clustering techniques for functional data are reviewed. Four groups of clustering algorithms for functional data are … consists of distance-based methods using clustering algorithms based on specific distances for functional data. A software …

reduction and inference for functional data. The selection of the number, d, of the FPC’s to be used in a specific procedure has … functional data can be sufficiently well approximated by a projection onto a finite-dimensional subspace, and the error resulting … increasing number of the FPC’s. Such an approach reflects more fully the infinite-dimensional nature of functional data, and …

important vehicle and reference point for the development and evaluation of robust methods in functional data analysis. In this …