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How R Took the World of Statistics by Storm

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Re: How R Took the World of Statistics by Storm

#41

Post by sampo »

jordigh wrote: post #2

I've regretted that Octave hasn't done for Matlab what R did for S. I understand some of the cirumstances that made this happen, but I'm deeply saddened of the entrenchment that Matlab has in scientific computing. It's getting chipped away little by little at the edges by Python, and to a lesser extent by Julia, but Matlab still is strong. And yes, some uses of Matlab can be replaced by R, but overall the two package…

> I've regretted that Octave hasn't done for Matlab what R did for S

R was much more programmable that the other systems (except S) in that time -- while the R language is not pretty, the scripting languages in SAS, Stata etc. were much worse. So R provided an improvement in people's workflow. Whereas Octave is just a free version of the same language as Matlab (with some small improvements).

So, switching from SAS, Stata, SPSS etc. to R provided an improvement in productivity, but switching from Matlab to Octave does not.

Re: How R Took the World of Statistics by Storm

#42

Post by jordigh »

sampo wrote: post #41
jordigh wrote: post #2

I've regretted that Octave hasn't done for Matlab what R did for S. I understand some of the cirumstances that made this happen, but I'm deeply saddened of the entrenchment that Matlab has in scientific computing. It's getting chipped away little by little at the edges by Python, and to a lesser extent by Julia, but Matlab still is strong. And yes, some uses of Matlab can be replaced by R, but overall the two package…

> I've regretted that Octave hasn't done for Matlab what R did for S R was much more programmable that the other systems (except S) in that time -- while the R language is not pretty, the scripting languages in SAS, Stata etc. were much worse. So R provided an improvement in people's workflow. Whereas Octave is just a free version of the same language as Matlab (with some small improvements). So, switching from SAS,…

You can make the same comparison between Fortran and Octave as you do betwenn SAS and R, and Octave at first did not even aim to be Matlab-compatible. Matlab compatibility came years later, as people using Matlab requested it.

This is not the reason for why Octave has not overtaken Matlab. Maybe I should write a blog post about it.

Re: How R Took the World of Statistics by Storm

#43

Post by _Wintermute »

anotheryou wrote: post #15

What would be a good start to learn this? I have some programming background and really would like to get into statistics. Should I do some R tutorial and throw my weblogs at it to see what I can do? Or is there some awesome learning resource you could share?

If you come from a programming background then Hadley Wickham's book is probably the best place to start.

http://adv-r.had.co.nz/

Re: How R Took the World of Statistics by Storm

#44

Post by KingMob »

plinkplonk wrote: post #9
outlace wrote: post #7

Earlier quoted context omitted.

I think Julia stands a really good chance at "chipping away" Matlab to a significant degree once it gets to a stable version 1.0 The syntax is close enough to Matlab to make the switch fairly easy, its got the performance, and the community has already developed a lot of cool scientific computing libraries even though each new version has breaking changes.

I think when Julia gets to 1.0, Matlab will begin to decline in use. I also think MathWorks is well aware of this "threat". The next few years will be interesting.

As someone who had to use a ton of Matlab in grad school, Julia's (and Python's) biggest issue in overtaking Matlab is replicating the large collection of battle-tested add-ons that Matlab offers.

Matlab is a crappy language, but a productive environment.

Re: How R Took the World of Statistics by Storm

#45

Post by KingMob »

joelthelion wrote: post #13
jordigh wrote: post #2

I've regretted that Octave hasn't done for Matlab what R did for S. I understand some of the cirumstances that made this happen, but I'm deeply saddened of the entrenchment that Matlab has in scientific computing. It's getting chipped away little by little at the edges by Python, and to a lesser extent by Julia, but Matlab still is strong. And yes, some uses of Matlab can be replaced by R, but overall the two package…

Numpy/Scipy (and Julia, maybe) are taking this role. There's really no reason to use Matlab these days.

If only that were true. There are many, many reasons to keep using Matlab, mostly toolboxes and decades of software written on top of it. As I said in another comment, Matlab is a bad language, but a productive environment.

In grad school, if I wanted to do my own EEG connectivity analyses, I could just include the Signal Processing Toolbox, the Stats Toolbox, and crunch my own numbers. Or, if I wanted to do a more standard analysis of my fMRI or EEG data, I would turn to the world's most popular open-source toolkits (SPM and Fieldtrip), both of which require... you guessed it, Matlab.

The only place I ever found Matlab's libraries deficient for my needs was in machine learning. (I ended up doing an SVM-based spotlight fMRI analysis in Python.)

There's a lot of lock-in and quality toolboxes around Matlab, Python/Julia won't knock it over yet, though I wish them the best of luck.

Re: How R Took the World of Statistics by Storm

#46

Post by KingMob »

frik wrote: post #11

R replaced SPSS. Octave replaced Mathlab. Python based libraries are somewhere in between. Julia with Jupyter will probably replace Mathematica, LabVIEW and Mathcad (and unify all of the above) with a powerful native language and environment.

???

R replaced S and S-PLUS, not SPSS. SPSS is still around as a light, user-friendly stats tool.

And Octave is nowhere near replacing Matlab, not by a long shot. It's the complete opposite story as R/S-PLUS.

Source: was in grad school for cognitive neuroscience. Saw Matlab everywhere. Saw SPSS here and there. Saw Octave nowhere. Briefly looked at Octave and stopped as soon as I realized all of the packages everyone used required Mathworks toolboxes.

Re: How R Took the World of Statistics by Storm

#47

Post by shele »

frik wrote: post #11

R replaced SPSS. Octave replaced Mathlab. Python based libraries are somewhere in between. Julia with Jupyter will probably replace Mathematica, LabVIEW and Mathcad (and unify all of the above) with a powerful native language and environment.

Mathematica is quite a different beast. It will be a while until julia has a native CAS and even then it will likely not be a CAS (Computer algebra system).

Re: How R Took the World of Statistics by Storm

#49

Post by ihnorton »

shele wrote: post #47
frik wrote: post #11

R replaced SPSS. Octave replaced Mathlab. Python based libraries are somewhere in between. Julia with Jupyter will probably replace Mathematica, LabVIEW and Mathcad (and unify all of the above) with a powerful native language and environment.

Mathematica is quite a different beast. It will be a while until julia has a native CAS and even then it will likely not be a CAS (Computer algebra system).

Still early days, but see http://www.nemocas.org/
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