Functional Data Analysis

A number of projects evolving from data in functional space.

Updated on September 08, 2022 by Surajit Ray

Random Functions Curve Clustering Mixture model Spectral Clustering

7 min READ

Functional data analysis is a growing field of research and has been employed in a wide range of applications ranging from genetics in biology to stock markets in economics. A crucial but challenging problem is clustering of functional data. In this thesis, we review the main contributions in this field and discuss the strengthens and weaknesses of the different clustering functional data approaches. We propose a new framework for clustering functional data and a new paradigm for model selection that is specifically designed for functional data, which are designed to address many of the weaknesses of existing techniques.


External Collaborators

Presentation at Banff Interntaional Research Station in 2015

Watch video on BIRS website | Download this video (77m)

Presentation at Royal Statistical Society Meetings 2013

RSS 2013 International Conference - Royal Statistical Society

Functional principal component analysis of spatially correlated data
Liu C., Ray S., and Hooker G. Statistics and Computing. 27 (6)
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Functional factor analysis for periodic remote sensing data
Liu C., Ray S., Hooker G., and Friedl M. Annals of Applied Statistics. 6 (2)
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