You might find this article useful
Kellie B. Keeling and Robert J. Pavur, A comparative study of the
reliability of
nine statistical software packages,
Computational Statistics & Data Analysis, Volume 51, Issue 8, 1 May 2007,
Pages
3811-3831.
(http://www.sciencedirect.com/science/article/B6V8
romocea
Sent: Tuesday, January 08, 2008 9:08 AM
To: [EMAIL PROTECTED]
Cc: r-help
Subject: Re: [R] I need arguments pro-S-PLUS and against SAS...
> John Sorkin wrote:
> The difference is not so much the language as the end users.
> S-Plus, R, SAS, etc. are all similar in that they are all to
the tools are not similar. The end _is_ the tool you use.
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Frank E Harrell Jr
> Sent: Monday, January 07, 2008 7:31 PM
> To: John Sorkin
> Cc: [EMAIL PROTECTED]
> Subject: Re: [R]
> errors in the data usually because I know the data. I find errors
> because I can say things like
>
> library(Hmisc)
> datadensity(mydata) # show all raw data in small rug plots
> hist.data.frame(mydata) # postage-stamp size histograms of all
> variables in dataset
> latex(describe(my
John Sorkin wrote:
> Frank,
> I believe you are proving my point. The difference is not so much the
> language as the end users. I use SAS, R, and SPlus on a regular basis. For
> some analyses, SAS is easiest to use, for some R (or SPlus). I can be just as
> dangerous using SAS and I can be with
Frank,
I believe you are proving my point. The difference is not so much the language
as the end users. I use SAS, R, and SPlus on a regular basis. For some
analyses, SAS is easiest to use, for some R (or SPlus). I can be just as
dangerous using SAS and I can be with R if I don't think about wha
John Sorkin wrote:
> I fear I risk being viewed as something of a curmudgeon, but the truth must
> be stated. S-Plus, R, SAS, etc. are all similar in that they are all tools to
> an end and not an end in themselves. Any one of the three can do most
> statistical analyses one might want to do. I
I fear I risk being viewed as something of a curmudgeon, but the truth must be
stated. S-Plus, R, SAS, etc. are all similar in that they are all tools to an
end and not an end in themselves. Any one of the three can do most statistical
analyses one might want to do. I could point out the strengt
SAS programming is easy if everything you want to do fits easily into the
row-at-a-time DATA step paradigm. If it doesn't, you have to write macros,
which are an abomination. DATA step statements and macros are entirely
different programming languages, with one doing evaluations at "compile" time
You might want to descibe what uses you expect to have
for SAS and/or R. It might make it easier for people
to make specific recommendations.
Personally I like the graphics, ease of writing
functions, and general ease of data manipulation.
--- Alberto Monteiro <[EMAIL PROTECTED]> wrote:
> I nee
One simple reason: graphic.
On Jan 5, 2008 5:23 AM, Liviu Andronic <[EMAIL PROTECTED]> wrote:
> On 1/4/08, Alberto Monteiro <[EMAIL PROTECTED]> wrote:
> > I need arguments pro-S-PLUS and against SAS for a meeting I will
> > have next week. S-Plus is (90 - 99)% compatible with R, so using
> > S-Pl
On 1/4/08, Alberto Monteiro <[EMAIL PROTECTED]> wrote:
> I need arguments pro-S-PLUS and against SAS for a meeting I will
> have next week. S-Plus is (90 - 99)% compatible with R, so using
> S-Plus will make things much easier for everyone. But I can't use
> this argument. What other arguments coul
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