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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.
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] I need arguments pro-S-PLUS and against SAS
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 tools to an
end
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,
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
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
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
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 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(mydata))
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 need
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 could I use?
Alberto Monteiro
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 could I
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-Plus will
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