Training in R

Revision as of 10:33, 24 February 2012

Upcoming training courses (R+OSGeo for spatio-temporal data analysis)

• 3-11 Sept 2012, Muenster (Germany): GEOSTAT
• June 11-22 2012, Zaragoza (Spain): Statistical analysis of geospatial data for environmental studies (course by Gerard Heuvelink and David G. Rossiter);
• April 1-3 2012, Wageningen: Sampling in space and time for survey and monitoring of natural resources, a 3-day course by Dick Brus;
• 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";

Regular courses/meetings

• 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;
• Paul Galpern, University of Manitoba, Winnipeg, 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

GEOSTAT icon

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.

To receive a notice about this summer school, please subscribe to the R-sig-geo mailing list, or send an e-mail to the course organizer, or insert a discussion point via this wiki.

The GEOSTAT 2011 summer school was held in IES Koblenz-Landau, Germany.

Figure: GEOSTAT 2011 Summer School, University of Koblenz-Landau, 25 July - 29 July 2011.

Figure: GEOSTAT 2010 Summer School, UNEX Plasencia, 27 June - 4 July 2010.

Figure: GEOSTAT 2009 Summer School, MEDILS Split, 3-10 May 2009.

Figure: GEOSTAT 2008 course for PhD students, University of Belgrade, 16-22 December 2008.

Figure: GEOSTAT 2008 Summer School, University of Amsterdam, 25-30 August 2008.

Figure: GEOSTAT 2007 School, Facolta di Agraria Napoli, 29.01-03.02.2007.

Teach-your-self literature

1. Beginners:
   • 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., 2011. R in Action: Data Analysis and Graphics with R. Manning publications, 472 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)
2. 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.