Journal article
Complementary co-kriging: spatial prediction using data combined from several environmental monitoring networks
Environmetrics (London, Ont.), Vol.16(3), pp.219-234
05/2005
DOI: 10.1002/env.699
Abstract
We consider the problem of optimal spatial prediction of an environmental variable using data from more than one sampling network. A model incorporating spatial dependence and measurement errors with network-specific biases and variances serves as the basis for the analysis of the combined data from all networks. We develop the associated optimal prediction methodology, which we call complementary co-kriging because (a) data from each network complements the other, and (b) the solutions to several prediction problems of interest are co-kriging predictors. A hypothetical example illustrates how much better the complementary co-kriging predictor can be, when compared to the ordinary kriging predictors from each network alone and to a 'naive' combined predictor. We use the methodology to obtain optimal predictions of wet nitrate concentration data over the eastern U.S. using data combined from the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) and the Clean Air Status and Trends Network (CASTNet). Copyright © 2005 John Wiley & Sons, Ltd.
Details
- Title: Subtitle
- Complementary co-kriging: spatial prediction using data combined from several environmental monitoring networks
- Creators
- Dale L Zimmerman - University of IowaDavid M Holland - Research Triangle Park Foundation
- Resource Type
- Journal article
- Publication Details
- Environmetrics (London, Ont.), Vol.16(3), pp.219-234
- DOI
- 10.1002/env.699
- ISSN
- 1180-4009
- eISSN
- 1099-095X
- Publisher
- John Wiley & Sons, Ltd
- Number of pages
- 17
- Language
- English
- Date published
- 05/2005
- Academic Unit
- Statistics and Actuarial Science; Biostatistics
- Record Identifier
- 9984257619902771
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