JSM 2005 Online Program

Abstract #304070

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:	395
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #304070
Title:	Jump Detection in Regression Surfaces Using Both First-order and Second-order Derivatives
Author(s):	Jingran Sun*+ and Peihua Qiu
Companies:	University of Minnesota and University of Minnesota
Address:	313 Ford Hall, School of Statistics, Minneapolis, MN, 55414, United States
Keywords:	Edge detection ; Image processing ; Jump location curves ; Nonparametric regression ; Surface estimation ; Threshold value
Abstract:	We consider the problem of detecting jump location curves of regression surfaces. In the literature, most existing methods detect jumps in regression surfaces based on estimation of either the first-order derivatives or the second-order derivatives of the regression surface. Methods based on the first-order derivatives are usually better in removing the noise effect, whereas methods based on the second-order derivatives are often superior in localization of the detected jumps. In this paper, we suggest a new procedure for jump detection in regression surfaces, which combines the strengths of the above two types of methods. Our method is based on estimation of both the first-order and second-order derivatives of the true regression surface. Theoretical justifications and numerical studies show it works well in applications.

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