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Please use this identifier to cite or link to this item: http://hdl.handle.net/2451/14791

Title: SPATIAL REGRESSION MODELS USING INTER-REGION DISTANCES IN A NON-RANDOM CONTEXT
Authors: Christou, Nicolas
Simon, Gary
Keywords: Hot spot
Kriging
Spatial prediction
Variogram
Issue Date: 2000
Publisher: Stern School of Business, New York University
Series/Report no.: SOR-2000-6
Abstract: This paper considers spatial data z, z(s2), z(sn) collected at n locations, with the objective of predicting z (s0) at another location. The usual method of analysis for this problem is kriging, but here we introduce a new signal-plus-noise model whose essential feature is the identification of hot spots. The signal decays in relation to distance from hot spots. We show that hot spots can be located with high accuracy and that the decay parameter can be estimated accurately. This new model compares well to kriging in simulations.
URI: http://hdl.handle.net/2451/14791
Appears in Collections:IOMS: Statistics Working Papers

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