Title: Functional Data Analysis: Prediction Through Canonical Correlation

Speaker: Ana Maria Kupresanin, Arizona State University

Date/Time: Thursday, February 26, 2009, 9:00 – 10:00am

Location: CSRI Building/Room 90 (Sandia NM)

Brief Abstract: With advances in technology, increased computing capability and capability to store more information, functional data now arise in a diverse and growing range of fields. Intuitively speaking, functional data represent observations of functions or curves. We study the problem of prediction and estimation in a setting where either the predictor or the response or both are random functions. We show that a general solution to the prediction problem in functional data can be accomplished through canonical correlation analysis. We also demonstrate that this abstract theory can be translated into practical tools for use in data analysis.

CSRI POC: Suzanne Rountree, (505) 844-4379