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R 3.0.0 Released 75

DaBombDotCom writes "R, a popular software environment for statistical computing and graphics, version 3.0.0 codename "Masked Marvel" was released. From the announcement: 'Major R releases have not previously marked great landslides in terms of new features. Rather, they represent that the codebase has developed to a new level of maturity. This is not going to be an exception to the rule. Version 3.0.0, as of this writing, contains only [one] really major new feature: The inclusion of long vectors (containing more than 2^31-1 elements!). More changes are likely to make it into the final release, but the main reason for having it as a new major release is that R over the last 8.5 years has reached a new level: we now have 64 bit support on all platforms, support for parallel processing, the Matrix package, and much more.'"
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R 3.0.0 Released

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  • by Anonymous Coward on Friday April 05, 2013 @04:32AM (#43366727)

    Someone who can't afford license fee of SAS or Matlab, this is the best alternative out there. And in some cases a better alternative.

    Not well known but R's accessibility support is far better. Here is an example from a paper accepted in R Journal

    Statistical Software from a Blind Person's Perspective
    A. Jonathan R. Godfrey


    • by Anonymous Coward on Friday April 05, 2013 @04:47AM (#43366767)

      It also feels more appropriate, somehow, to do research code in R: It's supposed to be shareable and reproducible, and using an expensive and proprietary language kind of defeats the purpose. Besides, CRAN and Bioconductor have rather a lot of useful stuff...

      • Re: (Score:2, Interesting)

        by Anonymous Coward

        Tell that to all the "scientists" and "researchers" paying money for _and_ investing lifetimes worth of effort into writing libraries for Matlab, Maple, Mathematica, LabView and other proprietary environments, instead of contributing to make the existing free environments better.

        Matlab --> GNU Octave, Scilab, NumPy/SciPy
        Maple, Mathematica --> Maxima, SymPy

        • by Anonymous Coward

          What about Axiom.

        • by Bill_the_Engineer ( 772575 ) on Friday April 05, 2013 @09:16AM (#43368075)

          Tell that to all the "scientists" and "researchers" paying money for _and_ investing lifetimes worth of effort into writing libraries for Matlab, Maple, Mathematica, LabView and other proprietary environments, instead of contributing to make the existing free environments better.

          Times are changing. There are many forces at work here:

          1. Cutbacks in funding is making lead scientists look for ways to save money.
          2. The proprietary vendors upgrading their software and charging license fees for each version (one particular vendor licenses specific minor versions).
          3. The desire to share work and non-proprietary methods are the best way to do it.
          4. New postdocs are familiar with python (they like working in iPython in particular) and its libraries.
          5. R is gaining ground with the older scientists due to its features and price.

          • Unfortunately, many scientists probably use commercial tools in hopes that their libraries will be picked up by the company and they will earn some money from it.

        • Also, there's Julia (http://julialang.org/ [julialang.org]), and I recently came across at least one IDE for it (although I haven't tried it yet): Julia Studio [forio.com].
        • by spike hay ( 534165 ) <blu_ice@violate. ... minus physicist> on Friday April 05, 2013 @10:11AM (#43368565) Homepage

          Drives me crazy. At least with statisticians, R is by far the dominant package now. But in science, it's Matlab Matlab Matlab.

          Python + Numpy/Scipy is such a better alternative now it's not even funny. It's actually a real language, and has loads of packages. And unlike Matlab, you don't have to pay extra money for additional packages (or any money).

          The use of closed source software in science is a waste of scarce resources, and it hurts openness. Another thing is that every numerical type class I've had has used Matlab. It's really unfair to expect students to purchase a copy. I use Octave when I have to deal with this, but it is not perfectly compatible.

          • Students have it good when it comes to matlab -- you can get a student version of matlab + simulink (with 10 or so toolboxes) for $99. The people who are really hurt by matlab's pricing schemes are the hobbyists who don't qualify for a student copy. There's this huge price dichotomy; when you're a student it's $99, after you graduate it's $5000+, and that's without any toolboxes.

            However, for academic use it makes perfect sense for scientists to use matlab over the alternatives. At least in the UC (universi

          • I tried switching to Python + Numpy/Scipy from Matlab. In the end I switched back to Matlab. I'm already familiar with python, and have done a lot of C++ programming so slight langauge differences were not the issue. Here are some of the reasons I switched back to Matlab:

            IDE Matlab comes with a ready to use IDE.

            Value semantics Matlab treats Matrices (and all classes that are not derived from "handle") using value semantics, so you know that Y=f(X) won't change X, if X is a matrix. However it also u

        • by rbprbp ( 2731083 )
          While I despise MATLAB for a large set of reasons, I agree that a large variety of toolboxes is available for pretty much anything you might want to do. And those are what most of the MATLAB users look for, in my experience: they might dislike the language, but MATLAB provides/they can purchase toolboxes that do what they need for their research.
        • by tlhIngan ( 30335 )

          Tell that to all the "scientists" and "researchers" paying money for _and_ investing lifetimes worth of effort into writing libraries for Matlab, Maple, Mathematica, LabView and other proprietary environments

          Depends on who they're doing it for, it seems. It's a time vs. money balance.

          In a commercial environment, Matlab tends to win out purely because of the toolboxes - especially current ones where Matlab has real-world interfaces so after modelling, you can prototype your control system with real hardware.

          • I haven't used labview, but Knime is both opensource and awesome. I can quickly prototype pretty much any workflow I want and get really good reproducibility. Debugging and unit tests need to be more directly integrated, but it is still a great package for practical science. It has R/Java/python integration as well!

          • by Anonymous Coward

            LabView is similar - a horrible mess if you want to program with it, but scientists and the like love it because it means not having to mess with code.

            I'm not sure "love" is the right word, at least in my experience. Although I've worked on several projects that used LabView, 90+% of the people working on it seemed to bitch and complain about it constantly. Many use it because they have already existing code using it, or because of equipment that has drivers that are much, much easier to use in LabView, or because in a few select cases, it lets you bang out a GUI control really quick. But otherwise, it seems to make the rest of the project a nightmare

    • by gajop ( 1285284 )

      I don't know about SAS, but Octave is a much better alternative to Matlab if money is your main issue.
      Hell even scilab or python's numpy are more similar.

    • by ceoyoyo ( 59147 ) on Friday April 05, 2013 @07:21AM (#43367299)

      I have a license for SAS through my university. I gave up trying to convince the stupid thing to install. If the installer wasn't crashing, the license manager was.

      MatLab has similar, though less severe problems.

      R had a nice double click installer that worked the first time. Later I compiled it, which worked without any headaches. There's a nice bridge from R to Python and you can extend either one, or embed either or both in other applications.

      You meant R has better accessibility options for the disabled but it's just plain more accessible.

      • by garcia ( 6573 )

        I am a SAS developer and have never run into any such problems but I won't say I don't believe you. However, the benefit of that large licensing fee is the easy access to SAS help resources (real live people living over there in Cary, NC) who get back to you VERY QUICKLY for ANY level of technical question you have.

        Their employees, at least the hundred or so I've met over the years when presenting at SAS Global Forum, have been INCREDIBLY friendly and helpful.

        • by ciurana ( 2603 )

          I am a SAS developer and have never run into any such problems but I won't say I don't believe you. However, the benefit of that large licensing fee is the easy access to SAS help resources (real live people living over there in Cary, NC) who get back to you VERY QUICKLY for ANY level of technical question you have.

          Their employees, at least the hundred or so I've met over the years when presenting at SAS Global Forum, have been INCREDIBLY friendly and helpful.

          If commercial software is your thing, and you can afford it, and the vendor offers good support, 100% agreed.

          If you're looking for R help the best two places to start are:

          * Get a copy of The R Book, by Crawley -- it'll save you days of pointless/incomplete search for web resources
          * Swing by the R IRC channel on Freenode (irc://irc.freenode.net/#R) -- we welcome n00bz



    • I once had a job in the EduBubble where I had to learn SAS. It's a language could only survive in the EduBubble, which is at least 15 years behind in technology and 25 years behind in thinking.

      If R isn't a well designed language, at least it is free, open source, and capable.

      • A couple of years ago I ran into SAS at a trade show. It really surprised me that they were still around; I'd previously seen their products on mainframes back in the late 70s, with punch cards. (I forget by now whether I'd used SAS or SPSS, which were the two competing commercial stats packages in that environment.)

  • by Anonymous Coward

    pie(c(85,15),init.angle=25,col=c("yellow",1),labels=c("pacman","not pacman"))

  • Buck lease && nun b sun
  • by golodh ( 893453 ) on Friday April 05, 2013 @06:12AM (#43367045)
    R's developers are, unlike many other Open Source developers, very careful about releasing production-quality software.

    As in: when they release it, you can trust it to work.

    Hence they didn't mess around with major reconstruction of R's guts until they could release something that's finished (and well-tested !) and bumped the version number to 3.0.0 when they did in order to properly differentiate it from previous versions.

    This is one of the differences between amateur OSS offerings (like for example KDE with its miriad half-baked Kxxx packages, sundry horrible OSS games, etc.) and genuine production-quality OSS (like R, Lapack, Octave, Libre Office, PostgressQL, MySQL, GRASS GIS, QGIS, Maria DB, GNU CC, the Linux kernel etc.)

    This is very gratifying as R happens to see widespread use in academia, government and business when it comes to data analysis and statistics.

    If R has a weakness, it is that uses an in-memory approach to data-processing, unlike e.g. SPSS, which keeps almost nothing in memory and simply makes passes through datafiles whenever it needs something. R is also a bit memory-hungry, so the need for genuine 64-bit implementations should be clear.

    Apart from sporting about 4000 useful and ready-to-run statistical applications packages, R has convenient and efficient integration with C code and has what's probably a contender for the best support for data-graphics anywhere.

    For those who didn't know, even packages like SPSS and SAS have incorporated R interfaces to tap into the wealth of application packages that R offers. Can't think of a more significant compliment right now.

    • by ciurana ( 2603 )

      LOL! Octave is a finished product? That's news to me. Horrible package when compared against R Project and its satellite projects (e.g. RStudio).

      Not trolling, just can't say that Octave is usable with a straight face. Poor UI, bad copy of MatLab, and horrible performance. Friends don't let friends use Octave. They show them the path to R.


  • Even i have used R in the past for my thesis. My statistician was using S-plus to do magical things that the hospitals SPSS definitely could not do.
    However, S-plus was not available to us non-statisticians.
    As a complete non-programmer, mediocre statistician, i was able to reproduce en build upon his examples in R.

    But what i truly missed was a usable GUI. there were some, and i tried them all at the time, but none were able to do more than the basics. For someone using R daily, a GUI will be more trouble and

    • There are no new GUIs in the R distribution, but there are several GUIs produced by third parties that probably weren't available when you were doing your thesis. I like RStudio and recommend it to my students, but there are others too.

      • I think you are confusing GUI with IDE; RStudio and most of the other R "guis" don't make R more discoverable. SPSS and the like are used because they offer guidance on what one should try given what they already know. With an IDE, you still have to know how to program. Throwing together a text editor, an output window, and an execution button doesn't do much.

        It's really disheartening that a professor thinks this solves any of the major pedagogical problems that R forces. I really wish you would STOP re

        • Yes, RStudio is an IDE. An IDE is a GUI for development. If you want a GUI to do statistics without programming, then RStudio is not what you need.

          I really don't know what you're talking about in your second paragraph. R doesn't force any pedagogical problems. It's a tool. It doesn't force anything.

    • by clark0r ( 925569 )
      I have recently implemented RStudio for a customer. http://www.rstudio.com/ [rstudio.com] It's a web interface for R which appears to be clean and easy to use. Installation was straightforward from RPM, you only need R-core, R-devel xdgutils and the rstudio RPM itself.
    • Re:GUI (Score:5, Informative)

      by golodh ( 893453 ) on Friday April 05, 2013 @07:11AM (#43367265)
      There are usable GUI's for R, and best of all: they can be installed as packages from within R.

      The best-known one is called 'R commander' (package name = Rcmdr ). It gives you a point-and-click interface and (like SPSS) drops the R code to repeat what you did using the menu (so that your work is reproducable).

      Functionality includes: data summaries, contingency tables, means tests, proportions tests, variance tests, ANOVA, cluster analysis, model fitting (linear, generalised linear, logit), various graphs, tests for comparison between fitted models, plus draws and lookup tables for lots of continuous and discrete distributions. Rcmdr allows for plugins, and a number of them are also downloadable as R packages (e.g. experimental design).

      The second one I know about is called 'Deducer' (package name Deducer), which provides a GUI loosely resembling that of SPSS.

      Both GUIs are workable and allow you to do simple things simply.

      There's also a rather nice IDE, called RStudio (which is a separate download).

      • R is an example of the best and worst of FOSS.

        Every time I switch institutions I can use it. No problem with lack of site license,no grant money for a license or activation problems on a new machine. I can use it on whatever OS the organization owns. I can get it up and running in about 5 minutes and it will work.

        Awsome community. If you have a problem there's a good chance there's something in the CRAN that solves it.

        But super steep learning curve. Begginner documentation is at best suboptimal ("go bu

        • I tend to agree about the learning curve.

          If you just use R to run data through a package (which in my opinion is the quickest way to get a lot of value out of R) then the learning curve is tolerable. Less steep than for SAS (I think), but steeper than for SPSS.

          On the other hand: R in and by itself is mostly a tool for statisticians and data analysts (or anyone else who doesn't flinch at having to write scripts, who's acquainted with the phenomenon of 'manual', and who's used to spending a few hours or s

      • R Studio is a nice interface and eased my transition from MATLAB to R.

Those who do not understand Unix are condemned to reinvent it, poorly. -- Henry Spencer