Nonparametric Spatial Prediction

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Let (ℕ*)N be the integer lattice points in the N-dimensional Euclidean space. We define a nonparametric spatial predictor for the values of a random field indexed by (ℕ*)N using a kernel method. We first examine the general problem of the regression estimation for random fields. Then we show the uniform consistency on compact sets of our spatial predictor as well as its asymptotic normality.

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