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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 414-425 |
| Number of pages | 12 |
| Journal | Technometrics |
| Volume | 53 |
| Issue number | 4 |
| DOIs | |
| State | Published - Nov 2011 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This research was partially supported by NSF grants DMS-1007504, CMG-0621118, and Award No. KUS-C1-016-04,made by King Abdullah University of Science and Technology(KAUST). The authors also thank the editor, associate editor,and two anonymous reviewers whose constructive commentshave greatly improved the presentation of the article.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
Keywords
- Hypothesis test
- Kriging
- Loss functions
- Model validation
- Prediction evaluation
- Wind power
ASJC Scopus subject areas
- Applied Mathematics
- Statistics and Probability
- Modeling and Simulation