Inefficiency of SAS Programming
Ajay ohri wrote:
why didnt you call it procunivariate if that was exactly what you wanted to do .....
Why would I ever do that? describe is a improvement on univariate, saving an estimated 87 +/- 87 trees per year in paper by printing what you need in much less space and concentrating on real descriptive statistics. Frank
On Tue, Mar 3, 2009 at 7:11 PM, Frank E Harrell Jr
<f.harrell at vanderbilt.edu <mailto:f.harrell at vanderbilt.edu>> wrote:
Ajay ohri wrote:
for an " inefficient " language , it sure has dominated the
predictive
analytics world for 3 plus decades.
I referred once to intellectual jealousy between newton and
liebnitz.
i am going ahead and creating the R package called "Anne".
It basically is meant only for SAS users who want to learn R ,
without upsetting the schedule of the corporate users.
Simply put , it is a wrapper on SAS language using the function
command...ie
procunivariate function in "Anne" package would call the summary
function
and so on...
Go ahead and add to the confusion. You've already created some by
using summary for procunivariate. I created the describe function
in the Hmisc package to replace univariate.
Frank
Regards,
Ajay
www.decisionstats.com <http://www.decisionstats.com>
On Tue, Mar 3, 2009 at 9:20 AM, Greg Snow <Greg.Snow at imail.org
<mailto:Greg.Snow at imail.org>> wrote:
This does not really address my point. Yes, if the few
nerds who want to
do funny stuff are the ones making the purchase, then there
is a good chance
(but still not guaranteed) that they will get IML, but do
all companies that
buy SAS actually think about that, or do they just see the
extra price (no
matter how low), or not even think to look at that piece
because the person
making the purchase does not really the funny things you can
do with it.
If you want your SAS code to be able to be run by anyone
with SAS, you
cannot assume that they have IML. If you want your R code
to be run by
anyone, you cannot make your code dependent on
packages/tools that are not
available for all platforms.
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org <mailto:greg.snow at imail.org>
801.408.8111
-----Original Message-----
From: Gerard M. Keogh [mailto:GMKeogh at justice.ie
<mailto:GMKeogh at justice.ie>]
Sent: Monday, March 02, 2009 3:22 AM
To: Greg Snow
Cc: Frank E Harrell Jr; R list;
r-help-bounces at r-project.org
<mailto:r-help-bounces at r-project.org>
Subject: Re: [R] Inefficiency of SAS Programming
Yes Greg,
but if you're buying SAS they'll throw in IML pretty
cheaply - SAS
think
it's only for a few nerds out there who wan to do funny
stuff.
G
Greg Snow
<Greg.Snow at imail.
org>
To
Sent by: "Gerard M. Keogh"
r-help-bounces at r-
<GMKeogh at justice.ie <mailto:GMKeogh at justice.ie>>, Frank E
project.org <http://project.org>
Harrell Jr
<f.harrell at vanderbilt.edu <mailto:f.harrell at vanderbilt.edu>>
cc
27/02/2009 19:05
"r-help-bounces at r-project.org
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Subject
Re: [R]
Inefficiency of SAS
Programming
But SAS/IML is not part of base SAS, it costs extra, so
there is a good
chance that a user that has SAS will not be able to run
code that uses
SAS/IML.
I have known of SAS programmers who know IML well that
still write
matrix/vector tools using macros or proc transpose so
that a user
without
IML can still use the code (the fact that the code that
started this
thread
was found on a website, suggests that it was meant for
general use
rather
than something only used internally where you know what
add-ons will be
available).
Just another way that R makes life easier for both
programmer and user.
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org <mailto:greg.snow at imail.org>
801.408.8111
-----Original Message-----
From: r-help-bounces at r-project.org
<mailto:r-help-bounces at r-project.org>
[mailto:r-help-bounces at r- <mailto:r-help-bounces at r->
project.org <http://project.org>] On Behalf Of
Gerard M. Keogh
Sent: Friday, February 27, 2009 7:19 AM
To: Frank E Harrell Jr
Cc: r-help-bounces at r-project.org
<mailto:r-help-bounces at r-project.org>; R list
Subject: Re: [R] Inefficiency of SAS Programming
Yes Frank, I accept your point but nevertheless IML
is the proper
place
for
matrix work in SAS - mixing macro-level logic and
computation is
another
question - R is certainly more seemless in this respect.
Gerard
Frank E Harrell
Jr
<f.harrell at vander
To
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"Gerard M. Keogh"
<GMKeogh at justice.ie <mailto:GMKeogh at justice.ie>>
27/02/2009 13:55
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Subject
Re: [R]
Inefficiency of SAS
Programming
Gerard M. Keogh wrote:
Frank,
I can't see the code you mention - Web marshall
at work - but I
don't
think
you should be too quick to run down SAS - it's a
powerful and
flexible
language but unfortunately very expensive.
Your example mentions doing a vector product in
the macro language
-
this
only suggest to me that those people writing the
code need a crash
course
in SAS/IML (the matrix language). SAS is
designed to work on
records
and
so
is inapproprorriate for matrices - macros are
only an efficient
code
copying device. Doing matrix computations in
this way is pretty mad
and
the
code would be impossible never mind the memory
problems.
SAS recognise that but a lot of SAS users remain
familiar with IML.
In IML by contrast there are inner, cross and
outer products and a
raft
of
other useful methods for matrix work that R
users would be familiar
with.
OLS for example is one line:
b = solve(X`X, X`y) ;
rss = sqrt(ssq(y - Xb)) ;
And to give you a flavour of IML's capabilities
I implemented a SAS
version
of the MARS program in it about 6 or 7 years ago.
BTW SPSS also has a matrix language.
Gerard
But try this:
PROC IML;
... some custom user code ...
... loop over j=1 to 10 ...
... PROC GENMOD, output results back to IML
...
IML is only a partial solution since it is not
integrated with the
PROC
step.
Frank
Frank E Harrell
Jr
<f.harrell at vander
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Subject
[R]
Inefficiency of SAS
Programming
26/02/2009 22:57
If anyone wants to see a prime example of how
inefficient it is to
program in SAS, take a look at the SAS programs
provided by the US
Agency for Healthcare Research and Quality for
risk adjusting and
reporting for hospital outcomes at
http://www.qualityindicators.ahrq.gov/software.htm
. The
PSSASP3.SAS
program is a prime example. Look at how you do
a vector product in
the
SAS macro language to evaluate predictions from
a logistic
regression
model. I estimate that using R would easily cut
the programming
time
of
this set of programs by a factor of 4.
Frank
--
Frank E Harrell Jr Professor and Chair
School of
Medicine
Department of Biostatistics
Vanderbilt
University
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Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University