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