The R vs Matlab vs S-Plus debate. Who wins according to Wilmott?

(Last Updated On: August 23, 2010)

The R vs Matlab vs S-Plus debate. Who wins according to Wilmott?

Interfaces to classic and feature rich C++ Quantlib library
Has more functions than S Plus
Not for beginners and need to learn a new programming language
Fairly slow and fails with extremely large datasets.
Need to spend two to three hours scouring forums and email lists to find complex routines
All command line
– R is free
– R will perform virtually all common statistical methods without additional programming
– R has graphics far superior to that of SAS and Excel, and rivals most other packages
– R is extensible. If you want to write C code and interface it with R, there is a simple way to do it
– R code/data written by you can be shared with the rest of the statistics community as an R package
– R documentation, including books, manuals, tutorials, etc. are freely available
A good choice for a programmer

Better interface than R

Close integration with Java
Well documented
Best interface of the three
More powerful than R
Allows simulations
Includes very useful toolboxes
Matlab is the preferred of the three
Matlab is for mathematicians while R is for statisticians
Fastest of the three. Twice as fast for matrices

This is what most people should look for when decideding on what programming language to go with:
The language should
• Have an intepreter for rapid prototyping, ease of debugging, and maximum fun.
• Have a native code (not just byte code) compiler that produces fast code that can be run stand-alone or be called from the interactive environment.
• Have good support for vectors, multi-dimensional arrays, strings, hash tables, etc. in the standard library.
• Have a free implementation.
• Work under linux and windows (so I can transfer code easily between my desktop and my laptop).
So I did some web searching and found lots of interesting stuff (see below).

From :

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