In recent years, several methods have been proposed to deal with functional data classification problems (e.g., one … for classifying functional data. This wavelet-thresholding semi-metric is able to adapt to the smoothness of the data and …

the integrated periodograms are curves, we apply functional data depth-based techniques to make the classification robust …

nearby time points. Functional data analysis methodologies have been developed to solve these type of problems. In order to … predict the class membership (multi-category response variable) associated to an observed curve (functional data), a …

parameters of a normal distribution are discussed, together with its relationship to functional data analysis and other standard …

, multivariate, panel and functional data. We also present real data examples which illustrate the utility of the surveyed results …

We explore the use of principal differential analysis as a tool for performing dimensional reduction of functional data … and effective representation of functional data, easily interpretable in terms of exponential, sinusoidal, or damped …-sinusoidal functions and providing a different insight to the functional data set under investigation. Moreover, in the analysis of the …

The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate …