Frede Aakmann Tøgersen
2014-Jun-06 13:21 UTC
[R] SAS VS R - What type of analysis is better?
Hi
SAS is famous for handling large data sets. For more than 10 years ago S+
introduced a module for large data sets. Never used it, more money for license
for a poor research institute.
Today I have a laptop with 8 Gb. If that's not enough then the head nodes on
our cluster has 64 Gb and some nodes 196 Gb.
But from time to time it could be an advantage to do some analysis using the
laptop.
So my question is: which kind of functionality for large data sets do the R
community offers?
Br.
Frede
Sendt fra Samsung mobil
-------- Oprindelig meddelelse --------
Fra: Frank Harrell
Dato:06/06/2014 14.43 (GMT+01:00)
Til: RHELP
Emne: Re: [R] SAS VS R - What type of analysis is better?
I can't think of an example where R does not work better than SAS except
for a few cases of mixed effects regression models and for processing
enormous datasets when the R user does not want to learn about the
latest R tools for large datasets. I quit using SAS in 1991 (in favor
of S-Plus and transitioned to R around 2000) and have never looked back.
Lately what has really made R powerful is its ability to interface
with other languages and especially the way it works in a reproducible
analysis/dynamic report document context.
Frank
--
Frank E Harrell Jr Professor and Chairman School of Medicine
Department of Biostatistics Vanderbilt University
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
Please do your homework. The place to start for questions like this is the CRAN Task Views page, where you will find a High Performance Computing topic that links here: http://cran.r-project.org/web/views/HighPerformanceComputing.html If nothing there suits, then re-post with details as to why not and what you think you are looking for. Cheers, Bert Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." H. Gilbert Welch On Fri, Jun 6, 2014 at 6:21 AM, Frede Aakmann T?gersen <frtog at vestas.com> wrote:> Hi > > SAS is famous for handling large data sets. For more than 10 years ago S+ introduced a module for large data sets. Never used it, more money for license for a poor research institute. > > Today I have a laptop with 8 Gb. If that's not enough then the head nodes on our cluster has 64 Gb and some nodes 196 Gb. > > But from time to time it could be an advantage to do some analysis using the laptop. > > So my question is: which kind of functionality for large data sets do the R community offers? > > Br. > > Frede > > > > > Sendt fra Samsung mobil > > > -------- Oprindelig meddelelse -------- > Fra: Frank Harrell > Dato:06/06/2014 14.43 (GMT+01:00) > Til: RHELP > Emne: Re: [R] SAS VS R - What type of analysis is better? > > I can't think of an example where R does not work better than SAS except > for a few cases of mixed effects regression models and for processing > enormous datasets when the R user does not want to learn about the > latest R tools for large datasets. I quit using SAS in 1991 (in favor > of S-Plus and transitioned to R around 2000) and have never looked back. > Lately what has really made R powerful is its ability to interface > with other languages and especially the way it works in a reproducible > analysis/dynamic report document context. > > Frank > -- > Frank E Harrell Jr Professor and Chairman School of Medicine > Department of Biostatistics Vanderbilt University > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.