Group for Research in Decision Analysis

# Clustering and classification of functional data

## Surajit Ray

Functional approaches to modeling dynamics of biological systems, trends in financial cycle, seasonal measurements of spectral bands in remote sensing, are becoming increasingly popular as a data analysis tool. On the other hand a recent approach aims at reducing the dimension of large $$p$$ small $$n$$ problems using a functional embedding of the $$p$$-dimensional vector (Talk by Hans-George Muller at JSM 2008). Clustering and classification is often an important final objective of functional data analysis, but most current techniques rely on a two step approach of first finding the functional basis and then performing clustering or classification based on these functions. In this research we will discuss the challenges and provide directions towards developing a comprehensive functional clustering approach. Applications in Landclass classification using remote sensing data will be presented during the talk.