Comparing Spatial Predictions

Amanda S. Hering*, Marc G. Genton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.
Original languageEnglish (US)
Pages (from-to)414-425
Number of pages12
JournalTechnometrics
Volume53
Issue number4
DOIs
StatePublished - Nov 2011
Externally publishedYes

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