> From: Tracy Harms
> 
> I've been asked how J compares to (and contrasts with) R. Because I've
> never used R my only option for a timely reply is to turn to others,
> so I'm passing this question on to the wider J community as I'm sure
> some of you have a better sense of what the answers can be.
> 
> If something along this line has already been written up, a pointer to
> it would be fine. If not, I think the overlap in target audience is
> great enough that it will be worth compiling some comparisons.
>

I don't know R anywhere as well as I know J, but given that disclaimer here are 
my impressions:

J 
 - strong mathematical focus
 - conceptual framework for working with array data is very general, consistent 
and well thought out.
 - code is succinct/terse
 - object-oriented paradigm available but optional

R
 - object-oriented paradigm is pervasive
 - strong statistical focus
 - mature/powerful plotting and graphics
 - larger user base
 - many user-contributed packages available
 - syntax for entering/manipulating arrays seems clumsy
 - code is relatively verbose
 - more accessible and extensive documentation

If my major focus was statistical then I think R would be the obvious choice. 
However I find J's data manipulation features to be both simpler and more 
powerful. 
So my current have-my-cake-and-eat-it-too solution is to use J for creating and 
manipulating data, then use its Rserve interface to access features/packages 
from R. However so far my R usage has been "light".

I found this post describing R interesting:
http://tolstoy.newcastle.edu.au/R/help/04/06/0388.html

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