From m1jjh00 at frb.gov  Thu Oct 20 01:25:50 2005
From: m1jjh00 at frb.gov (Jeffrey J. Hallman)
Date: Wed, 19 Oct 2005 19:25:50 -0400
Subject: [Rd] [R-gui]  R GUI considerations (was: R, Wine,
	and multi-threadedness)
In-Reply-To: Message from Kasper Daniel Hansen <khansen@stat.Berkeley.EDU> 
	of "Wed, 19 Oct 2005 15:53:38 PDT."
	<250C8EE4-98EA-48D2-8372-F952A3E9E827@stat.berkeley.edu> 
Message-ID: <20051019232550.9E3B953585@mail.rsma.frb.gov>

>>>>> "K" == Kasper Daniel Hansen <khansen at stat.Berkeley.EDU> writes:
  K> On Oct 19, 2005, at 3:43 PM, Jeffrey J. Hallman wrote:

  K> <SNIP>

  >> Think about it.  Once you have a basic math package that can handle  
  >> matrix
  >> programming and various mathematical functions, building the various
  >> statistical modeling tools on top of them is not that hard.  What  
  >> makes S and
  >> R so much better than SAS is their programmability.  Smalltalk is  
  >> like that,
  >> only better.
  >> 
  >> 
  >> Jeff Hallman

  K> I would claim that this quote kind of shows that you have no idea  
  K> what you are talking about regarding good, debugged and trustworthy  
  K> statistical procedures. Why do you think people are actually using R?

Kasper, a few minutes spent Googling my name should disabuse you of the notion
that I have no idea of what I'm talking about.  But to answer your question: 
I think people are using R because it's readily available, with a lot of good
stuff already built in.  

I am not suggesting that you tell undergraduate statistics students to write
everything in Smalltalk, since the class libraries to support statistical
programming in Smalltalk do not exist yet.  What I am saying is that if you
compare the languages themselves, along with their programming environments,
Smalltalk is superior to R.  What it lacks are class libraries implementing
statistical procedures.  I do maintain that those really are not that hard,
once you have the matrix and math libraries.  My experience with S and R goes
way back to the days of blue book S version 3.  S called out to C code to
handle matrix and mathmetical stuff, but used S code itself to glue it all
together in a somewhat object-oriented way. 

  K> I could say "well, given an environment that could interface to C,  
  K> building a GUI on top of that is not really that hard", but that  
  K> would be incredible naive as well.

Indeed it would be.  But statistical programming is easier than that.


Jeff



[Rd] [R-gui] R GUI considerations (was: R, Wine, and multi-threadedness)
Jeffrey J. Hallman