Abstract
Spatial and spatio-temporal data are everywhere. Besides those we collect ourselves (‘is it raining?’), they confront us on television, in newspapers, on route planners, on computer screens, on mobile devices, and on plain paper maps. Making a map that is suited to its purpose and does not distort the underlying data unnecessarily is however not easy. Beyond creating and viewing maps, spatial data analysis is concerned with questions not directly answered by looking at the data themselves. These questions refer to hypothetical processes that generate the observed data. Statistical inference for such spatial processes is often challenging, but is necessary when we try to draw conclusions about questions that interest us.
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Notes
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Particulate matter smaller than about 10 μm.
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A steep learning curve – the user learns a lot per unit time.
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CRAN mirrors are linked from http://www.r-project.org/
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Mostly the authors of this book with help from Barry Rowlingson and Paulo J. Ribeiro Jr.
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Reprinted in 2004.
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Bivand, R.S., Pebesma, E., Gómez-Rubio, V. (2013). Hello World: Introducing Spatial Data. In: Applied Spatial Data Analysis with R. Use R!, vol 10. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7618-4_1
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