Details of Grant 

EPSRC Reference:	GR/R55375/01
Title:	Mixed Effects Models For Functional Data
Principal Investigator:	Chatfield, Dr C
Other Investigators:	Walker, Professor SG
Researcher Co-Investigators:
Project Partners:
Department:	Mathematical Sciences
Organisation:	University of Bath
Scheme:	Standard Research (Pre-FEC)
Starts:	15 September 2001	Ends:	14 December 2001	Value (£):	6,342
EPSRC Research Topic Classifications:	Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:
Summary on Grant Application Form
Mixed effects models are a popular and effective tool for analysing data with a grouped or hierarchical structure. A wide variety of methods exist for the analysis of scalar and multivariate responses. The purpose of the proposed research is to develop some parallel methodology for the modeling of functional responses. The particular application in mind is the modeling of human motion data. Human movements can be recorded using motion capture technology and the three-dimensional coordinates of markers on specified locations on the body can be tracked over time. The resulting data is necessarily discrete in time, but is recorded at such high frequency that it can be regarded as functional. Functional regression models can be used to explain and predict this motion in terms of predictors such as the height of the person. We propose to develop mixed effects models for functional data that will explain the fixed effects of predictors such as height and gender, while incorporating random effects related to between and within subject variability. Analogous data arise in many other fields, such as environmental science and finance, and give rise to multiple time-series data with a hierarchical structure. When the low frequency variation of these series is of greatest interest, the methodology being developed should be useful.
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Organisation Website:	http://www.bath.ac.uk