Progress in technology (connecting objects, monitoring devices, sensors, remote sensing, neuroimaging, etc.) makes it possible to collect data in some sort of continuum. The continuum may be related to time or space, but could also originate from multiple sources. In those problems, a statistical unit may be a curve, a surface or any complex mathematical object. Such data are called functional data and the technology to analyze and model them is termed Functional Data Analysis (FDA).
The goal of FDA is to extract information from such complex data to understand key features of the data and to make statistical inference and predictions. An intrinsic feature of functional data is that they are infinite dimensional data, so dimension reduction and regularization are often needed to facilitate the analysis. This poses challenges but also opens opportunities. The success of this exciting modern area of Statistics is mainly due to its ability to solve major hi-tech engineering challenges coming from important domains of applications (biology, biomechanics, chemometric, econometrics, environmental management, geophysics, image processing, medicine, remote sensing, etc) while raising new methodological and theoretical issues.
This international FDA specialized team aims to promote developments and advances for FDA in all spectrum