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Some theory for point-referenced data models
| Content Provider | Scilit |
|---|---|
| Author | Banerjee, Sudipto Carlin, Bradley P. Gelfand, Alan E. |
| Copyright Year | 2014 |
| Description | The intent of this chapter is to provide a brief review of the basic theory of stochastic processes needed for the development of point-referenced spatial data or geostatistical models. We begin with the development of spatial stochastic processes built from independent increment processes, with particular interest in stationary spatial processes. We briefly discuss the connection between covariance functions and spectral measures. We discuss the validity of covariance functions as well as simple constructions of valid covariance functions. We then turn to smoothness of process realizations as driven by stationary covariance functions with a brief discussion of directional derivative processes (anticipating a fuller discussion in Chapter 12). Next, we expand our development of isotropic covariance functions. We conclude with a section on nonstationary covariance specifications. Book Name: Hierarchical Modeling and Analysis for Spatial Data |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2009-0-07095-7&isbn=9780429137174&doi=10.1201/b17115-7&format=pdf |
| Ending Page | 95 |
| Page Count | 20 |
| Starting Page | 76 |
| DOI | 10.1201/b17115-7 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2014-09-12 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Hierarchical Modeling and Analysis for Spatial Data Statistics and Probability Models Stochastic Theory Covariance Functions Referenced |
| Content Type | Text |
| Resource Type | Chapter |
