Asymptotic normality of kernel estimates in a regression model for random fields

Mohamed El Machkouri and Radu Stoica

Journal of Nonparametric Statistics, 2010, vol. 22, issue 8, 955-971

Abstract: We establish the asymptotic normality of the regression estimator in a fixed-design setting when the errors are given by a field of dependent random variables. The result applies to martingale-difference or strongly mixing random fields. On this basis, a statistical test that can be applied to image analysis is also presented.

Date: 2010
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Citations: View citations in EconPapers (6)

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DOI: 10.1080/10485250903505893

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