This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 25
Type: Topic Contributed
Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #306563
Title: A Jump-Detecting Procedure Based on Spline Estimation
Author(s): Lijian Yang*+ and Shujie Ma
Companies: Michigan State University and Michigan State University
Address: Department of Statistics and Probability, East Lansing , MI, 48824, USA
Keywords: B spline ; knots ; jump points ; nonparametric regression ; asymptotic p-value ; upcrossing probability

In a random design nonparametric regression model, procedures to detect jumps in the regression function via constant and linear spline estimation method are proposed based on the maximal differences of the spline estimators among neighboring knots, the limiting distributions of which are obtained when the regression function is smooth. Simulation experiments provide strong evidence that corroborates with the asymptotic theory, while the computing is extremely fast. The detecting-procedure is illustrated in analyzing the thickness of pennies data set.

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