JSM 2004 Online Program

Abstract #301252

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Activity Number:	113
Type:	Contributed
Date/Time:	Monday, August 9, 2004 : 10:30 AM to 12:20 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #301252
Title:	Functional Regression for Clustered Data
Author(s):	Yolanda Munoz Maldonado*+
Companies:	Texas A&M University
Address:	Department of Statistics, College Station, TX, 78743-3143,
Keywords:	functional data ; regression curves ; clustered data ; smoothing splines ; Kalman filtering
Abstract:	Functional regression analysis is studied in a clustered data setting. We propose a general approach for estimating regression curves using spline smoothing type methods that are suitable for such an environment. Efficient algorithms to compute these estimators are developed via use of the Kalman Filter. The algorithms are implemented using the SAS PROC STATESPACE procedure. Run-time comparisons are performed between this approach and an alternative mixed models implementation using SAS PROC MIXED.

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