JSM 2005 Online Program

Abstract #304496

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	131
Type:	Topic Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Biometrics Section
Abstract - #304496
Title:	Far Casting Crossvalidation in Correlated Data Model Selection
Author(s):	Patrick Carmack*+ and William R. Schucany and Richard Gunst and Jeffrey Spence and Qihua Lin
Companies:	The University of Texas Southwestern Medical Center at Dallas and Southern Methodist University and Southern Methodist University and The University of Texas Southwestern Medical Center at Dallas and Southern Methodist University
Address:	5323 Harry Hines Blvd, Dallas, TX, 75390-8896, United States
Keywords:	cross validation ; cv ; model selection ; time series ; spatial ; correlation
Abstract:	Moderate to highly correlated data presents a special problem for ordinary cross validation in terms of model error assessment. Withholding the point of prediction still leaves heavily correlated neighbors in the prediction process, which even poorly fitting models can use to essentially recoup the withheld data. Far casting crossvalidation reduces this optimism by also withholding adjacent neighbors in the prediction step while leaving them in the model estimation process, which generally leads to better model selection. Application to spatially correlated brain image data is explored.

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