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GEOSTAT tutorials

GEOSTAT software

Software iconList of FOSS software used in this course and installation instructions. Follow these instructions to prepare and customize the software before the beginning of the course.

Literature used

ASDAR bookList of books / lecture notes used in this course. See also: CRAN Task View: Analysis of Spatial Data.


« February 2017 »

Smith: Basic methods for Areal/Spatially Aggregated Data

Date & time: Wednesday 19 August 2015, 09.00-12.30

Objective: Introduction to exploratory methods and models for area-level count data.

General description: I will start with some examples of area-level data from epidemiology. Then I will introduce methods for estimating and testing spatial autocorrelation.  Finally I will go through basic spatial smoothing models and how to fit them in R. Slides and materials are available from

Required back-ground knowledge: basics of statistical modeling, a general understanding of regression and glms, familiarity with Bayesian inference would be helpful

Software / R packages required: sp, spdep, SpatialEpi, R-INLA (not on CRAN, see


9:00–10:30 Overview of statiical methods for areal data;

10:30–11:00 Coffee break;

11:00–12:30 Examples with spdep, SpatialEpi, R-INLA using gastrointestinal illness data (or your own data)


  • Bivand, R. S., Pebesma, E. J., Gomez-Rubio, V., and Pebesma, E. J., Applied spatial data analysis with R. New York: Springer, 2008. (Chapters 9 and 10)
  • Banerjee, S., Carlin, B. P., and Gelfand, A. E. Hierarchical modeling and analysis for spatial data. CRC Press, 2014.  (Chapters 4 and 6)
  • Blangiardo, M. and Cameletti, M. Spatial and Spatio-temporal Bayesian Models with R-INLA. John Wiley & Sons, 2015. (Sections 6.1 and 6.2)


Lancaster University Campus (Conference centre / George Fox Building) Lancaster, LAN
United Kingdom
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