Training in R
Upcoming training courses
- 23 Jan - 02 March 2012, Enschede: Geostatistics & Open-source statistical computing, Distance education course by David G. Rossiter;
- fall 2011, University of Manitoba, Winnipeg, Canada: R for Landscape Ecology Workshop Series;
- 12-16 December 2011, Wageningen: Geostatistics;
- 24-25 October 2011, Wageningen: Introduction to R for Statistical Analysis;
- 17-21 October 2011, Wageningen: Uncertainty propagation in spatial and environmental modelling;
- 18-24 September 2011, Belgrade: R+OSGeo in education (5 day course for PhD students);
- 10-11 September 2011, Redlands CA: Automated analysis of Automated analysis of DEMs using R+OSGeo (workshop at Geomorphometry 2011);
- 16-18 August 2011, Warwick, Coventry, UK: Use R 2011 offers several tutorials on using new packages;
- 24-31 July 2011, GEOSTAT 2011, IES Koblenz-Landau;
- 3-10 May 2011, Bergen: "Analysing spatial data", intensive course for PhD students;
- 11-17 April 2011, Geosciences Australia, Canberra: "Using R+OSGeo to process environmental data";
- 21-22 March 2011, IfGI, University of Muenster: Workshop on spatio-temporal data in R;
- 25-29 October 2010, Alterra, Wageningen University: PE&RC post-graduate course "Geostatistics";
- 12-13 October 2010, Web-inars on using R for monitoring Natural Resources run via USGS;
- 20(-23) July 2010, Gaithersburg, Maryland, USA: Spatial Statistics tutorial at useR! 2010 conference;
- 5-16 July 2010, University of Amsterdam, Summer Courses Geo-ecological Data Analysis (SCGE-2010);
- 27 June - 4 July 2010, Plasencia, Spain: GEOSTAT 2010 Summer School for PhD students;
- 28 June - 7 July 2010, Copenhagen, Denmark: Ph.D. Summer School - Use of open source tools for spatial ecological modelling;
- 4 April - 5 May 2010, Department of Animal Breeding and Genetics, Aarhus, Denmark: Geostatistics and GIS course;
- 8-12 March 2010, Soil and Water Science Department, Gainesville, Florida: Short course on Geostatistical Analysis of Environmental Data;
- 13 January - 28 April 2010, Statistical and Applied Mathematical Sciences Institute, Raleigh, USA: Course in Spatial Statistics in Climate, Ecology and Atmospherics;
- 29-30 August 2009, University of Zurich, CH: "Automated analysis of elevation data in R+SAGA/GRASS";
- 31 August - 4 September 2009, Academy for PhD Training in Statistics, UK: "Spatial and Longitudinal Data Analysis" by P.J. Diggle;
- 7 July 2009, Agrocampus Ouest, Rennes, FR: half-day training tutorials in various new R packages;
- 16-18 June 2009, University of Southampton, UK: "Hierarchical modelling of spatial and temporal data: a 3-day course"; a one-day meeting on environmental and spatial statistics is scheduled for 16 June;
- 3–10 May 2009, MEDILS, Split, Croatia: GEOSTAT 2009 Summer School;
- 16-17 March 2009, Sheraton Palo Alto, California, USA: "Statistical learning and data mining" - a two-day course by T. Hastie and R. Tibshirani;
- spring 2009, e-Workshop hosted by Global GIS Academy "Spatial analysis in R";
- Aarhus Universiteit, DK: Courses from the Research Unit of Bioinformatics, Genetics and Statistics;
- Academy for PhD Training in Statistics, UK
- Arizona State University, USA: The GeoDa Center for Geospatial Analysis and Computation e-learning courses;
- Bioconductor workshops;
- CSISS, University of California, Santa Barbara: Advanced Spatial Analysis workshops;
- Copenhagen University, DK: Hands-on training courses on spatial ecological modeling using R, GRASS and other open source tools;
- The University of Manchester, UK: CCSR Short Courses;
- University of Muenster, DE: IfGI Spring school;
- Global GIS academy e-learning courses;
- Lancaster University, UK: Short courses: R;
- Mango Solutions, UK: The R Language courses;
- Imperial college London, UK: Introduction to R courses;
- ITC, Enschede, NL: Geostatistics and Open-Source Statistical Computing (distance education course);
- useR! conferences (includes also workshop and training sessions);
- USGS web-inars on using R for monitoring natural resources;
- University of Oregon, Dept. Geography, USA: Geographic Data Analysis Using R courses;
- Wageningen University and Research, NL: PE&RC Postgraduate Courses;
People in Academia running courses on R
- Roger Bivand, NHH, Bergen, Norwey;
- Gilberto Câmara, National Institute for Space Research, Brasil;
- Bendix Carstensen, Department of Biostatistics, University of Copenhagen, Denmark;
- Ole Christensen, Aarhus Universitet, Denmark;
- Peter Dalgaard, University of Copenhagen, Denmark;
- Jerome H. Friedman, Standford University, USA;
- John Fox, McMaster University, Hamilton, Canada;
- Trevor Hastie, Standford University, USA;
- Robert Hijmans, University of California, Davis, USA;
- Gerard B.M. Heuvelink, Wageningen University and Research, NA;
- Matthew C. Keller, University of Colorado, Boulder, USA;
- Petra Kuhnert, CSIRO, Australia;
- Michael Lachmann, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany;
- Edzer Pebesma, Universität in Münster, Germany;
- David G. Rossiter, ITC, Enschede, NL;
- Martin Theus, University of Augsburg, Germany;
Geostat 5-DAY training courses
The author of this website regularly organizes (with a group of colleagues: Gerard B.M. Heuvelink, Edzer Pebesma, Victor Olaya Ferrero, Roger Bivand, Olaf Conrad) a 5-days training course entitled "Spatio-temporal data analysis with R + SAGA + Google Earth". The objective of the course is to provide training to junior researchers interested to use R-based tools for analysis of spatially and temporally referenced data. The course is non-commercial, which implies that none of the lecturers is contracted or will receive any financial awards. The course consists of a balanced combination of theoretical and practical training and includes a one-day workshop where each participant can present their case studies and receive a valuable feedback.
The GEOSTAT 2011 summer school was held in IES Koblenz-Landau, Germany.
- Beaudette, D., 2009. Open Source Software Tools for Soil Scientists, University of California at Davis.
- Braun, W.J., Murdoch, 2008. A First Course in Statistical Programming with R. Cambridge University Press, Cambridge, 174 p. ISBN 9780521694247
- Crawley, M.J., 2005. Statistics: An Introduction using R. John Wiley & Sons, Ltd. ISBN 0470022973
- Everitt, B.S., Hothorn, T., 2006. HSAUR: A Handbook of Statistical Analyses Using R. Chapman & Hall/CRC, 325 p.
- Kabacoff, R.I., 2009. Data Analysis and Graphics with R. Manning publications, 375 p. ISBN 9781935182399
- Kuhnert, P., Venables, W.N., 2005. An Introduction to R: Software for Statistical Modelling & Computing. CSIRO Canberra, Australia, 362 p.
- R Development Core Team, 2008. An Introduction to R. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3900051127
- Venables, W.N., Smith, D.M., R Development Core Team, 2004. An Introduction to R. Network Theory Ltd, 156 p. ISBN 0954161742
- see also: Books on R
- USGS R course materials (teach yourself)
- Spatial data analysis/visualization in R:
- Baddeley, A., 2008. Analysing spatial point patterns in R. CSIRO Canberra, Australia.
- Bivand, R., Pebesma, E., Rubio, V., 2008. Applied Spatial Data Analysis with R. Use R Series, 400 p. Springer, Heidelberg, p. 378.
- Diggle, P.J., Ribeiro Jr, P.J., 2006. Model-based Geostatistics. Springer Series in Statistics, 230 p.
- Reimann, C., Filzmoser, P., Garrett, R., Dutter, R., 2008. Statistical Data Analysis Explained Applied Environmental Statistics with R. Wiley, Chichester, 337 p.
- Theus, M., Urbanek, S., 2008. Interactive Graphics for Data Analysis: Principles and Examples. CRC Press, 277 p.