Model-Based Geostatistics the Easy Way

Patrick E. Brown

Journal of Statistical Software, 2015, vol. 063, issue i12

Abstract: This paper briefly describes geostatistical models for Gaussian and non-Gaussian data and demonstrates the geostatsp and dieasemapping packages for performing inference using these models. Making use of R’s spatial data types, and raster objects in particular, makes spatial analyses using geostatistical models simple and convenient. Examples using real data are shown for Gaussian spatial data, binomially distributed spatial data, a logGaussian Cox process, and an area-level model for case counts.

Date: 2015-02-13
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Citations: View citations in EconPapers (3)

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https://www.jstatsoft.org/index.php/jss/article/do ... mapping_1.1.5.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v063i12/v63i12.R

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:063:i12

DOI: 10.18637/jss.v063.i12

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