Measuring Departure from Gaussian Assumptions in Spatial Processes
In this paper entropy is presented as an alternative measure to characterize the Divariate distribution of a stationary spatial process. This non-parametric estimator attempts to quantify the concept of spatial ordering, and it provides a measure of how gaussian the experimental bivariate distribution is.
The concept of entropy is explained and the classical definition presented. In particular, the reader is reminded that, for a known mean and covariance, the bivariate gaussian distribution maximizes entropy. A “relative entropy” estimator is introduced in order to measure departure of an experimental bivariate distribution from the bivariate gaussian.
KeywordsEntropy Covariance Fluor Kriging
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