R: advanced statistical package

About R
R is a general-purpose, command-line based, environment for working with data. R is based on a functionalapproach to working with vectors and matrices of data. R is a convenient environment for processing, analyzing, and plotting data.

Soils-Related R Packages
The 'aqp' (Algorithms for Quantitative Pedology) package was developed to facilitate numerical extensions to classical studies of soil geography, genesis and classification. [CRAN] [R-Forge]

R in the News

• NY Times article (2009-01-07)
• Follow-up Blog posting to NY Times article (2009-01-07)
• R in the blog-o-sphere (c/o google)

Getting Started

• Paul Geissler's excellent R tutorial
• Dave Robert's Excellent Labs on Ecological Analysis
• Excellent Tutorials by David Rossitier
• Excellent tutorial an nearly every aspect of R (c/o Rob Kabacoff)
• Introduction to R by Vincent Zoonekynd
• R Cookbook
• Data Manipulation Reference
• R time series tutorial
• R Concepts and Data Types presentation by Deepayan Sarkar
• Interpreting Output From lm()
• The R Wiki
• An Introduction to R
• Import / Export Manual
• R Reference Cards
• KickStart
• Hints on plotting data in R
• Regression and ANOVA
• Appendices to Fox Book on Regression
• JGR a Java-based GUI for R [Mac|Windows|Linux]
• A Handbook of Statistical Analyses Using R(Brian S. Everitt and Torsten Hothorn)

Searching for Information

• RSeek
• R Site Search

R with Geographic Data

• Geographically weighted regression
• Geostats with geoR
• DCluster, splancs, spdep and spatstat packages available on CRAN
• GRASS6 - R Interface
• Interesting thread on the use of kriging variance

Misc. Articles

• Some Reasons NOT to use Excel for Stats
• When Summary Stats Aren't Enough
• Why "dynamite plots" are a bad idea
• Many examples of plotting data in R
• Notes on R
• Scientific Graphing applications
• Ideas on how to make more informative axis in a plot
• Tips on R graphics
• Color space visualization

Pages in Section

• Access Data Stored in a Postgresql Database
• Additive Time Series Decomposition in R: Soil Moisture and Temperature Data
• Aggregating SSURGO Data in R
• Cluster Analysis 1: finding groups in a randomly generated 2-dimensional dataset
• Color Functions
• Comparison of Slope and Intercept Terms for Multi-Level Model
• Comparison of Slope and Intercept Terms for Multi-Level Model II: Using Contrasts
• Creating a Custom Panel Function (R - Lattice Graphics)
• Customized Scatterplot Ideas
• Estimating Missing Data with aregImpute() {R}
• Exploration of Multivariate Data
• Interactive 3D plots with the rgl package
• Making Soil Property vs. Depth Plots
• Numerical Integration/Differentiation in R: FTIR Spectra
• Plotting XRD (X-Ray Diffraction) Data
• Using lm() and predict() to apply a standard curve to Analytical Data
• Working with Spatial Data
• Comparison of PSA Results: Pipette vs. Laser Granulometer