R is much faster than Splus and it's open-source. I suggest using R unless there is a particular capability available only in Splus. My sense is that more and more statisticians are moving to R, and that this will become the standard in future years, with packages being developed for R rather than for Splus.

- Getting started
- Data objects, memory, and speed
- Initialization
- Memory management in S
- Reading gzipped, bzipped, zipped, and url files into R

- Interacting with the Operating System
- Calling UNIX commands from within S/R
- Batch/indirect operation
- Manipulating the working directory in R
- Unfreezing R

- Resetting the seed
- Stopping on a warning
- Working with objects
- Working indirectly with objects based on text strings (computing on the language):
- Listing and sizing your objects:
- Scope (i.e., dealing with object names within functions)
- Pointers and passing by reference in R

- Graphics and output
- Graphics devices
- Formatting screen output
- Outputting tables to Latex
- Saving graphics as postscript files
- Saving graphics as pdf files in R
- Saving graphics in other formats in R
- Using Greek letters and other manipulations in figure labels, etc.
- Nice dots/points in scatterplots
- Placing multiple labels in the outer margin
- Miscellaneous graphics commands

- Spatial and spatio-temporal data and methods
- Image plots for displaying spatial observations
- Working with shape files and neighborhood structures in R
- Space-time smoothing in R
- Universal kriging and generalized least squares (GLS) fitting
- Standard errors in gam(), spm(), geoR in R
- Using gamm()
- User-defined variance functions in gamm() and lme()
- Mapproj package (mapproject) problems

- Database type operations
- Merging datasets
- Matching elements between vectors
- Sorting matrices and dataframes
- Doing calculations on subgroups of data

- Distribution-related functions
- QQ plot confidence intervals
- Regressing multiple outcomes on the same explanatory variables
- If/else syntax issues
- Libraries in R
- Installing R libraries locally on your system
- Calling BUGS from within R
- Using C, C++, and Fortran within R and Splus
- Speed

Chris Paciorek 2012-01-21