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

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

2009-07-09

arxiv.org/abs/0907.1519v1

Mathematics

Statistics Theory

20 pages

Scientific paper

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.

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