Data in many different experiments cannot be described by a single numerical value but through a curve. In most of situations, from a statistical view point, these curves can be considered as random elements in an appropriate functional space that usually is a separable Hilbert space. This is the case of functional data obtained by continuous/sparse-time/spatial monitoring processes, or of fuzzy data obtained through sociological surveys, to name but a few. Applications are found in industrial processes as well as in different sciences, such as econometrics, medicine, sociology, biostatistics, bioinformatics, environmetrics, geophysics, chemometrics, etc.

This track is concerned with the statistical analysis of functional data and more generally of random elements in Functional and separable Hilbert spaces.