**Statistical Graphics and more » R**, and kindly contributed to R-bloggers)

R did definitely not start to be THE statistical computing tool. The “two Rs” in far down-under just needed some tool which was not too expensive and structured enough to support the elementary statistics classes filled with hundreds of students. Another constraint was the computing lab which was large enough, but “only” filled with Mac IIs.

As the “two Rs” were computer savvy and knew the S-language, they started with a simple copy of the basic functionality of the S-language. Everything else which happened since the early 90s is history by now.

There are quite a few tools and languages which managed to set fundamental standards like Postscript, pdf, LaTeX, Java, etc. but, e.g., C++ didn’t offer inline Java or the formula editor in Word did not get a LaTeX compatible mode.

Not so for R.

The list of applications which connect to R and support the utilization of R functions in some way is quite long already, and seems to get new prominent members every now and then:

**SAS**

allows using R-code within IML (despite the initially quite aggressive take on R)**SPSS**

supports writing R code for several versions now**Statistica**

has R integration**JMP**

uses the power of R**Oracle**

just released their own R package R-ODM to use Oracle data mining functions from within R.- …

Certainly, with Rserve it is more or less a piece of cake to talk to R for anyone who knows the basics of programming, but companies like SAS and Oracle are quite big players, who usually care a xxxx about what other projects and/or standards do.

In some sense it looks like the Goliaths start to surrender to the David, although he never really attacked …

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**Statistical Graphics and more » R**.

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