Spatial Process Estimates - IMAGe

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Kriging with a fixed part

Adding a fixed component

g(x) = ∑ i

φ i (x)d i + h(x)

d is fixed

h is a mean zero process with covariance, k.

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Kriging with a fixed part Adding a fixed component g(x) = ∑ i φ i (x)d i + h(x) d is fixed h is a mean zero process with covariance, k. 10

BLUE/Universal Kriging Find d by Generalized least squares ˆd = ( T T M −1 T ) −1 T T M −1 y M = K + λI ”Krig” the residuals ĥ = K(K + λI) −1 (y − T ˆd) 11

Page 1 and 2: Spatial Process Estimates SAMSI Sum
Page 3 and 4: The additive model Given n pairs of
Page 5 and 6: A review of the conditional normal
Page 7 and 8: The Kriging weights Conditional dis
Page 9: My geostatistics/BLUE overhead For
Page 13 and 14: The spline connection Basis functio
Page 15 and 16: Identifying a covariance function T
Page 17 and 18: Correlations among ozone In many ca
Page 19 and 20: 50 Sensitivity to the covariance Ex
Page 21 and 22: 140 140 140 140 140 140 140 140 140

Spatial Process Estimates - IMAGe

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