A new definition of depth for functional observations is introduced based on the notion of "half-region" determined by a curve. The half-region depth provides a simple and natural criterion to measure the centrality of a function within a sample of curves. It has computational advantages...

A popular approach for classifying functional data is based on the distances from the function or its derivatives to group representative (usually the mean) functions or their derivatives. In this paper, we propose using a combination of those distances. Simulation studies show that our...

We propose using the integrated periodogram to classify time series. The method assigns a new element to the group minimizing the distance from the integrated periodogram of the element to the group mean of integrated periodograms. Local computation of these periodograms allows the application...

A natural methodology for discriminating functional data is based on the distances from the observation or its derivatives to group representative functions (usually the mean) or their derivatives. It is proposed to use a combination of these distances for supervised classification. Simulation...

We propose notions of simplicial band depth for multivariate functional data that extend the univariate functional band depth. The proposed simplicial band depths provide simple and natural criteria to measure the centrality of a trajectory within a sample of curves. Based on these depths, a...