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I know this is not precisely a programming question, but I don't where else to ask...
S-PLUS was aquired by TIBCO some years ago. And it was seemingly included to the Spotfire product. However I installed the demo version of Spotfire and can't find anything indicating that S-PLUS is anymore part of it.
So my question is: is S-PLUS dead? And is there any way to install a prior version of it? I know R has totally taken over, but I'd be curious to just try it out if it is available somewhere.
Not sure how relevant the question is but here are my $0.02:
Yes, R has won.
TIBCO still seems to have a Spotfire product mentioning S-Plus (pdf found via simple Google search).
IIRC, years ago TIBCO purchased the commercial S license, but it turns out that nobody really wanted S-Plus if it was not entirely compatible with R.
TIBCO learned that lesson and built an entirely new R-compatible engine they call TERR; the jury is still out as to whether it will ever get any significant traction.
In the end, it is rather difficult to beat a well-maintained and written Open Source product---and R is one of the better examples of Open Source done right.
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(Edited to narrow the question to Ada. Have posted other questions for Fortran and COBOL.)
I've spent some time in the past year dealing with changes to my code due to Python v2->v3 and R v3->v4 changes. It got me curious as to some of the older languages that are still in use.
I know Ada still sees occasional updates and functionality upgrades. I would assume that their mission-critical nature makes those changes smaller and more backward-compatible, but I don't really know and couldn't find it with a web search.
What and when were the last changes to Ada that was on the same rough order as the Python 2->3 changes?
Ada pays a lot of attention to reverse compatibility, to avoid breaking existing code, when making changes.
Last formal Ada release was Ada-2012, there is another one (Ada-202X) in progress.
Ada-2012 has a lot that Ada-83 doesn't, but I'd be surprised if there was anything more than trivial work to build an Ada-83 project (or Ada-95 or Ada-2005) in Ada-2012.
There are some differences though : from Ada-83 to Ada-2012 As you can see, there's really not much to say for 30 years of development.
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I am not able to find any definitive answer to what problem Julia solves compared to the two languages, I was told are most commonly used in working with data (data science), R and Python.
I am not asking for any opinions. Please support replies with factual information (sad I need to add this but it seems some people think this topic is opinion based).
Could anyone explain this?
The Julia Programming Language solves the same problems as R and Python. However, it can solve them extremely faster than those mentioned above, as it runs over C code and uses a JIT compiler. See the Julia Benchmark. This and other advantages that can be found at the language site, it's Twitter profiles: Julia Computing and Julia Language.
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I have looked around and have not found many opinions on if it is important to update your R software as soon as a new version is released.
Any opinions would be welcomed!
As with any software, you should carefully evaluate what is included in any new release. If the release consists only of bug-fixes, it is usually expedient to install it as soon as it is practicable for you to do so. If the scope of the release is more expansive -- new features, etc. -- you should review the release more carefully.
If you're in the middle of an important project with a killer deadline, it's quite reasonable to wait a little while before applying any update.
Also, you should as a matter of routine re-run a selection of jobs, that you know the answers to, in order to be sure that the answers are still the same. "No, mistakes of this nature don't happen often, but they do happen."
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This is a very basic question, but since I am new to R and I am starting to learn it now, I am buying this book.
http://www.amazon.in/Cookbook-OReilly-Cookbooks-Paul-Teetor/dp/0596809158
Now, after reading the sampler available on the internet, I found out that all the examples are given in R but I use Rstudio. I just wanted to know that the same instructions and syntax will work in Rstudio as well, right?
Thanks!
Basically - yes. RStudio is (only) the IDE (Integrated development environment - http://en.wikipedia.org/wiki/Integrated_development_environment) for R.
Hovewer, R Cookbook is from 2011, so it's recipes depend on quite old R version. It's possible, that some of recipes won't work, not because of using RStudio, but because of using newer R version.
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The question is in the Title. Basically I'm looking for an alternative to R.
I've been using R a bit, there are some really good stuff about it (especially data.frame plyr and ggplot), however I really love Haskell and type inference, so I was wondering if using Haskell to do "simple" statistic analysis would be a good choice.
My basic needs are :
read/write CSV
import SQL table
do some basic 'mapReduce' on the data. Which where R is great but I assume Haskell should be equally good.
However my experience with Haskell is everything is fine until you process realworld data. You always encounter performance issue (and soonish) because even though in theory you should write functional code and don't worry about what's the computer is doing, if you don't and don't use the appropriate library and are not an Haskell expert, stuff are damned slow.