JSM 2004 Online Program

Abstract #300192

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Activity Number:	4
Type:	Invited
Date/Time:	Sunday, August 8, 2004 : 2:00 PM to 3:50 PM
Sponsor:	Business and Economics Statistics Section
Abstract - #300192
Title:	Infinite Order Kernels and Nonparametric Regression
Author(s):	Tim McMurry*+ and Dimitris Politis
Companies:	University of California, San Diego and University of California, San Diego
Address:	Department of Mathematics, La Jolla, CA, 92093-5004,
Keywords:	integrated time series ; tapered bootstrap ; unit root testing
Abstract:	The usefulness of infinite order kernels in nonparametric regression and autoregression will be discussed. Smoothing with infinite order kernels leads to estimators with minimal bias and an optimal rate of convergence over an appropriate class of smooth functions. In addition, it allows for a bandwidth selection process which adapts to the smoothness of the underlying function. Aided by infinite order kernels, applications of the bootstrap to constructing improved confidence bands for nonparametric regression will also be presented.

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