Computation in proximal soil sensing with 'R' - Google Groups
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and Graphics by W. N. Venables, D. M. Smith and the R Core Team (accessible via http://cran.r-project.org/doc/manuals/R-
Computation in proximal soil sensing with ‘R’ – introduction and applications Dr. Michael Schirrmann
About the seminar ‘R’ a is free statistical programming environment. Due to its support by a large community including the finest statisticians it has become a sophisticated software package. In the seminar you will learn how to use ‘R’ for analysis of proximal soil sensing data. The focus is on giving you an overview of the ‘R’ environment on beginner level. The seminar covers practical issues in statistical computing which includes data handling in ‘R’, reading data into ‘R’, creating data graphics, writing ‘R’ functions as well as specific tasks related to proximal soil sensing like modelling of spatial data and multivariate calibration of spectrometry data. For practical training with ‘R’ we will use real world examples.
Seminar content • • • • • •
Overview of ‘R’ and the IDE ‘RStudio’ Data handling in ‘R’: Importing and exporting data, data manipulation Descriptive statistics and graphical representation of data Introduction to spatial analysis in ‘R’ Introduction to multivariate data analysis in ‘R’ Specific working examples for geostatistical analysis of spatial data with the ‘R’ package ‘gstat’ and multivariate calibration using the package ‘plsr’
Time and Venue 30 May 2013, 9:00 to 16:00 h Leibniz-Institute for Agricultural Engineering, Max-Eyth-Allee 100, 14469 Potsdam, Germany
Registration Information The maximum number of participants is limited to 16 persons. The seminar is free of charge for attendees of the Global Workshop of Proximal Soil Sensing 2013.
Requirements The seminar is dedicated to beginners and no pre-knowledge of R is expected. Basic programming skills and statistical experience are advantageous. In order to follow the
examples, participants should bring their own laptop computer with the software ‘R’ and ‘RStudio’ pre-installed.
Suggested Readings There is no specific textbook required for this seminar. However, there is a large community and lots of helpful books related to R available. Suggested readings for this seminar might include: •
• • •
An Introduction to R - Notes on R: A Programming Environment for Data Analysis and Graphics by W. N. Venables, D. M. Smith and the R Core Team (accessible via http://cran.r-project.org/doc/manuals/R-intro.pdf) Applied Spatial Data Analysis with R by Roger S. Bivand, Edzer Pebesma and Virgilio Gomez-Rubio (Springer) Multivariate Statistical Analysis in Chemometrics by Kurt Varmusa and Peter Filzmoser (CRC Press) Software for Data Analysis: Programming with R (Statistics and Computing) by John M. Chambers (Springer)
