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September, 1993 Kernel-Type Estimators of Jump Points and Values of a Regression Function
J. S. Wu, C. K. Chu
Ann. Statist. 21(3): 1545-1566 (September, 1993). DOI: 10.1214/aos/1176349271

Abstract

In the fixed-design nonparametric regression model, kernel-type estimators of the locations of jump points and the corresponding sizes of jump values of the regression function are proposed. These kernel-type estimators are analyzed with almost sure results and limiting distributions. Using the limiting distributions, we are able to test the number of jump points and give asymptotic confidence intervals for the sizes of jump values of the regression function. Simulation studies demonstrate that the asymptotic results hold for reasonable sample sizes.

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J. S. Wu. C. K. Chu. "Kernel-Type Estimators of Jump Points and Values of a Regression Function." Ann. Statist. 21 (3) 1545 - 1566, September, 1993. https://doi.org/10.1214/aos/1176349271

Information

Published: September, 1993
First available in Project Euclid: 12 April 2007

zbMATH: 0795.62043
MathSciNet: MR1241278
Digital Object Identifier: 10.1214/aos/1176349271

Subjects:
Primary: 62G05
Secondary: 62G20

Rights: Copyright © 1993 Institute of Mathematical Statistics

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Vol.21 • No. 3 • September, 1993
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