Abstract In this chapter, Section 4.1 briefly introduces the history of geostatistics. Section 4.2 explains stationary spatial processes and the basic geostatistical model to describe the process; Section 4.3 explains how to estimate the model parameters. After introducing Kriging, which is the spatial interpolation approach, in Section 4.4, Section 4.5 introduces its extensions including linear and non-linear kriging approaches. Then, Sections 4.6, 4.7, and 4.8, respectively, explain semiparametric, Bayesian, and spatiotemporal extensions of the geostatistical approach. Finally, Section 4.9 explains geostatistical approaches for large samples.
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Geostatistics and Gaussian process models
Semantic Scholar · Mathematics · 2020
Abstract
Abstract In this chapter, Section 4.1 briefly introduces the history of geostatistics. Section 4.2 explains stationary spatial processes and the basic geostatistical model to describe the process; Section 4.3 explains how to estimate the model parameters. After introducing Kriging, which is the spatial interpolation approach, in Section 4.4, Section 4.5 introduces its extensions including linear and non-linear kriging approaches. Then, Sections 4.6, 4.7, and 4.8, respectively, explain semiparametric, Bayesian, and spatiotemporal extensions of the geostatistical approach. Finally, Section 4.9 explains geostatistical approaches for large samples.