期刊
SPATIAL STATISTICS
卷 7, 期 -, 页码 1-20出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.spasta.2013.11.001
关键词
Geostatistics; Nugget effect; Ordinary kriging; Semivariogram; Spatial count data
类别
资金
- College of Business at The University of Texas at San Antonio
- National Science Foundation [DMS-1208896, HRD-0932339]
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1208896] Funding Source: National Science Foundation
This work revisits a simple geostatistical model for the analysis of spatial count data and describes some of its main second-order properties. This geostatistical model is simpler than an alternative hierarchical model, also used for the analysis of spatial count data, so it may be more appealing to practitioners and spatial data analysts. Geostatistical methods for trend parameter estimation, semivariogram estimation and prediction of the latent process are reviewed, and new estimators and predictors are proposed. Finally, a designed simulation experiment is carried out to investigate and compare the sampling properties of the different estimators and predictors. (C) 2013 Elsevier B.V. All rights reserved.
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