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How the R-project is taking over statistical analysis software
- dj_axl 15y agoAnecdotally, NumPy (Python) has some traction. Similarly they don't consider SQL libraries. And I'm sure there are statistical analysis libraries for Java. According to the bar chart below R is mentioned by 45%, SQL by 32%, Python by 25%, Java by 24%. This seems a more reasonable comparison to me than the graphs earlier (higher up) in the post. https://sites.google.com/site/r4statistics/_/rsrc/1318535062528/popularity/Fig_6_KDnuggetsPollLanguages.PNG https://sites.google.com/site/r4statistics/_/rsrc/1318535062...
- UrbanPat 15y agoWhat do you mean by "SQL Libraries"? Do these interface with SQL to perform analysis?
- ginzasparrow 15y agoDIE SAS DIE
- eftpotrm 15y agoHaving worked on and off with SAS in recent years I'm aware it has its limitations, but round here we like constructive contributions please. Would you like to expand upon your remarks?
- aditya 15y agoCan someone point me to a good introduction/resources to R? Especially for web stuff?
- jsavimbi 15y agoI keep an eye on R-bloggers: http://www.r-bloggers.com/ http://www.r-bloggers.com/
- roxtar 15y agoI like this site: http://www.statmethods.net/ http://www.statmethods.net/
- Arjuna 15y agohttp://cran.r-project.org/other-docs.html http://cran.r-project.org/other-docs.html
- csmt 15y agoR in Nutshell is pretty good book: http://shop.oreilly.com/product/9780596801717.do http://shop.oreilly.com/product/9780596801717.do
- linhir 15y agoI do a good bit of R programming, and R in a Nutshell has been the best quick reference guide I have found.
- SkyMarshal 15y agohttp://www.reddit.com/r/rstats http://www.reddit.com/r/rstats http://stackoverflow.com/tags/r/info http://stackoverflow.com/tags/r/info
- ahalan 15y agohttp://www.quora.com/What-are-essential-references-for-R http://www.quora.com/What-are-essential-references-for-R
- traveldotto1 15y agolove R.. but have to say because it's open source, you do have to watch for the quality of libraries
- burgerbrain 15y agoSurely that would still be the case under any license.
- traveldotto1 15y agoyes.. but for less adopted or emerging platforms, you have to be more conscious of the source of the library, and should look at the source to verify its functionalities
- burgerbrain 15y agoThis still has nothing to do with the licensing of the software.
- pyoung 15y agoHe is probably comparing R to SAS (which are the two most popular statistical programming languages). SAS doesn't really have libraries, instead you buy additional packages from SAS, which are very reliable and well supported, but expensive. My company shuns R (although I personally like it), primarily because of this issue. If we need to run a rare or uncommon statistical procedure, it is a lot easier to trust the SAS procedure, rather than an open source R package written by some grad student.
- TalGalili 15y agoTrue, Though if you need to run a rare or uncommon stat procedure, SAS is not likely to have it in the core, and then you are back to using what "some grad student wrote".
- eastwest 15y agoI am shunning SciPy and to a less extent NumPy for the same reason. I have reason to believe the developers are not experts in numerical linear algebra and some of the documentation also do not lend confidence.
- dewarrn1 15y agoI use R as my primary data-analysis tool for almost all of my work, with occasional recourse to SAS for certain specialized models (e.g., PROC GLIMMIX for generalized mixed models). My only complaint is the awful default IDE, which can be mitigated to a large extent by scripting elsewhere and source()ing the script, and some odd edge behaviors including the mystifying row names of dataframes, the difficulty of dropping unused factor levels from aggregated or sliced data (another dataframe issue), and the perhaps unnecessary obscurity of some of the plotting functions (although holding R responsible for the lattice library is unfair). All that said, for a free tool, it's extraordinary, and the authors of the base language and the many packages that I use have my gratitude.
- roxtar 15y agoDefault IDE? Do you mean the R interpreter REPL? If you are looking for a nice IDE for R, I would suggest RStudio: http://rstudio.org/ http://rstudio.org/
- dennish00a 15y agoI love R--but I end up using Stata more often because it is easier to produce vector graphics that can be imported to Illustrator. I wish that the R community would start to focus on graphics.
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- migiale 15y agoUnfortunately, it's almost impossible to work with a very large datasets in R, because of the speed limitations. Many researchers I know use Matlab because of this.
- hvs 15y agoWhat about Octave? Other than my use in the Stanford Machine Learning class, I've never really used either, so I don't have any basis for comparison.
- rflrob 15y agoMy recollection is that Octave is significantly slower than Matlab, and some quick googling on benchmarks [1] suggests that it is (was?) as slow or slower than R. I've complained before that Octave is the wrong solution to the Matlab problem, and if you aren't attached to one of the many fine Matlab toolkits, you're likely better served translating to a more expressive language, like Python+Numpy+Scipy. [1] http://sciviews.org/benchmark/ http://sciviews.org/benchmark/
- migiale 15y agoOctave is Matlab clone, in fact Octave developers openly say that except for some special cases, any difference between Octave and Matlab is a bug. The biggest difference between Matlab and Octave is JIT compiler in Matlab, which does incredibly good job at vectorizing simple (or sometimes even not-so simple) loops. I think it's fair to say that Octave performance is very close to a Matlab in a pre-JIT time. There's also a huge difference in toolboxes, profiling, sparse matrix operations, parallel computing and many-many more. In these areas I'm afraid Octave is light-years behind Matlab. However, you still can do a lot of useful simple stuff with Octave and it's free! Matlab-like syntax is really, really cool then it comes to vectorized operations. So probably these two reasons determined Andrew Ng's choice of Octave as a main environment for ml-class. Huge win for Octave I guess. This might spur some interest in the development, attract new people to the product. I think it's a well-deserved success for John W Eaton and other people who develop(ed) Octave all these years.
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- 6ren 15y agoI think open-source eventually replaces commercial products, in the same way that proprietary products become commoditized. The response for commercial products is also the same: continual differentiation, adding new features, benefits, support, documentation etc. Exceptions are also the same: natural monopolies (e.g. strong network effects). Open-source is great at hill-climbing, where there are clear directions for improvement and especially for features that are obviously needed by users (provided the structure of the project is sufficiently modular to facilitate it), by tapping the collective intelligence of users. It's not great at "hill-hopping": originating radically different products.
- cageface 15y agoCounter-examples abound. Can you name even one open source app that has displaced a mature, user-facing desktop app with a non-trivial UI, other than a web browser? Open source only seems to win in domains in which it makes sense for companies to share work in order to compete at a higher tier of functionality.
- 6ren 15y agoYou skipped the bit about differentiation: if, for example, photoshop didn't keep improving, do you think the gimp would never catch up? I think you could find lots of examples where today's open source version is better than an x-years-old proprietary product. The only way it realistically can realistically happen if is the commercial product is not being improved (i.e. differentiated) any more. Your example is one of these - standardization is related to commodification. I suspect also that user-facing apps are easier to keep improving, because the user is right there, and always has more needs that could be served (e.g. text editors will evolve til they can read mail; those that can't will be replaced by those that can). Non-user facing apps tend to be defined by their environment, rather than by users - although, any component that creates a benefit that the user wants more of will keep being improved (from Clayton Christensen). e.g. databases, CPUs.
- sandGorgon 15y agoVLC
- lemming 15y agoModerately related - has anyone who previously used R in a serious way switched over to Incanter? Is Incanter comparably powerful?
- georgieporgie 15y agoLooks interesting, but that page renders only on the right half of my Android screen, and can't be zoomed or reflowed.
- jcdreads 15y agoProbably worth noting about the author: > Robert A. Muenchen is the author of R for SAS and SPSS Users and, with Joseph M. Hilbe, R for Stata Users. He is also the creator of r4stats.com, a popular web site devoted to helping people learn R. Bob is a consulting statistician with 30 years of experience Disclaimer: I hate R's syntax, but my company's analytics group uses R for just about everything.
- zzleeper 15y agoI started learning SAS (I mostly use stata/matlab/python for my daily needs) but also ended up abhorring some parts of the syntax..
- dfc 15y agoIf R did a little more hand holding it would be awesome.