Exploratory Analysis of Functional Data via Clustering and Segmentation

Exploratory Analysis of Functional Data via Clustering and Segmentation

Abstract:

Functional data arise in numerous practical contexts. Spectrometry is a well known example in which each observation is described by a spectrum: a function that maps wavelengths to absorbance values. A more general example is given by time series data: each object is described by the evolution through time of several quantities, represented by a function that map time to the associated values. Applications of this paradigm range from online monitoring to joint time series prediction.