B-spline estimation of regression functions with errors in variable

Ja-Yong Koo and Kee-Won Lee

Statistics & Probability Letters, 1998, vol. 40, issue 1, 57-66

Abstract: This paper proposes a new B-spline method for nonparametric regression function estimation which can be applied to the case even when the covariate is contaminated with noise. A property of B-splines, reproducing line property, is crucial in the construction of B-spline estimators for regression function. To account for errors in covariate, deconvolution is involved in the construction of B-spline estimators. It is shown that the B-spline estimators achieve the optimal rate of convergence which depends on the tail behavior of the characteristic function of the error distribution.

Keywords: Characteristic; function; Deconvolution; Fourier; transform; Reproducing; line; property; Rate; of; convergence (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (2)

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