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Journal article
Correcting for informative sampling in spatial covariance estimation and kriging predictions
Journal of geographical systems, Vol.25(4), pp.587-613
10/2023
Web of Science ID: WOS:001056286200001
Abstract
Informative sampling designs can impact spatial prediction, or kriging, in two important ways. First, the sampling design can bias spatial covariance parameter estimation, which in turn can bias spatial kriging estimates. Second, even with unbiased estimates of the spatial covariance parameters, since the kriging variance is a function of the observation locations, these estimates will vary based on the sample and overestimate the population-based estimates. In this work, we develop a weighted composite likelihood approach to improve spatial covariance parameter estimation under informative sampling designs. Then, given these parameter estimates, we propose three approaches to quantify the effects of the sampling design on the variance estimates in spatial prediction. These results can be used to make informed decisions for population-based inference. We illustrate our approaches using a comprehensive simulation study. Then, we apply our methods to perform spatial prediction using real estate data across a metropolitan area.
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Details
- Title
- Correcting for informative sampling in spatial covariance estimation and kriging predictions
- Publication Details
- Journal of geographical systems, Vol.25(4), pp.587-613
- Resource Type
- Journal article
- Publisher
- Springer Nature
- Number of pages
- 27
- Grant note
- National Institute of Statistical Science The work of the authors was supported by the National Institute of Statistical Science.
- Copyright
- © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature
- Identifiers
- WOS:001056286200001; 99381289039506600
- Academic Unit
- Hal Marcus College of Science and Engineering ; Mathematics and Statistics
- Language
- English