Hi, I am doing a very informal presentation for my office about R capabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/OneMapProdWithRGraphics.html together with examples of my own work. I am finishing with pros and cons about R and I am wondering if you can come up with other examples, or comments. Here they are: Pros: - R is a programming environment well suited for statistical analysis. - R is open source and cross platforms (Windows, Mac, Linux). - Fortran, C (C++), and Python wrappers are in place. - Deals well with spatial data, has a robust graphical interface and has an active user group list / forum. - External packages for R are almost daily increasing, most of them based on published up-to-date books and peer-reviewed articles. - R related books ? quite a few ?. Cons: - R has a very steep learning curve. - There is no perfect ?beginner? book. - Experience with other programming languages is a plus / minus. - You can save scripts, but not *.exe. - It is updated several times a year (good) but there are no up-grades. - It seems that it is hard to install correctly under Linux. - Everything you want to do is a command line, minimal GUI. - Memory management problems (depends on your OS), especially when displaying big images at high resolution or working with huge matrices (hundreds of Mb). Also i am wondering if R works under 64 bit computers and if it takes advantage of it. Thanks, Monica _________________________________________________________________ Refresh_family_safety_052008
On Thu, May 22, 2008 at 5:00 PM, Monica Pisica <pisicandru at hotmail.com> wrote:> - It seems that it is hard to install correctly under Linux.Actually, it is quite easy to install R under Linux, at least in some distributions. For instance, on Fedora: yum install R R-devel and that is it. Paul
Monica Pisica wrote:> > Cons: > > - R has a very steep learning curve.I don't think the learning curve is any steeper than SAS programming, it is just a different kind of curve. -- Kevin E. Thorpe Biostatistician/Trialist, Knowledge Translation Program Assistant Professor, Department of Public Health Sciences Faculty of Medicine, University of Toronto email: kevin.thorpe at utoronto.ca Tel: 416.864.5776 Fax: 416.864.6057
What do you mean, "there are no up-grades?" There are 1,401 ancillary packages - all free. That sounds like upgrades to me. Of course there is no *perfect* beginner's book, but Peter Dalgaard's Introductory Statistics with R (Paperback), Springer, 3d printing edition (January 9, 2004) is pretty close. If you don't know much statistics, it will teach you statistics while teaching you R. If you already know statistics, it will demonstrate how to do familiar things using R. Charles Annis, P.E. Charles.Annis at StatisticalEngineering.com phone: 561-352-9699 eFax: 614-455-3265 http://www.StatisticalEngineering.com -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Monica Pisica Sent: Thursday, May 22, 2008 12:00 PM To: r-help at r-project.org Subject: [R] Pros and Cons of R Hi, I am doing a very informal presentation for my office about R capabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/O neMapProdWithRGraphics.html together with examples of my own work. I am finishing with pros and cons about R and I am wondering if you can come up with other examples, or comments. Here they are: Pros: - R is a programming environment well suited for statistical analysis. - R is open source and cross platforms (Windows, Mac, Linux). - Fortran, C (C++), and Python wrappers are in place. - Deals well with spatial data, has a robust graphical interface and has an active user group list / forum. - External packages for R are almost daily increasing, most of them based on published up-to-date books and peer-reviewed articles. - R related books - quite a few .. Cons: - R has a very steep learning curve. - There is no perfect "beginner" book. - Experience with other programming languages is a plus / minus. - You can save scripts, but not *.exe. - It is updated several times a year (good) but there are no up-grades. - It seems that it is hard to install correctly under Linux. - Everything you want to do is a command line, minimal GUI. - Memory management problems (depends on your OS), especially when displaying big images at high resolution or working with huge matrices (hundreds of Mb). Also i am wondering if R works under 64 bit computers and if it takes advantage of it. Thanks, Monica _________________________________________________________________ Refresh_family_safety_052008 ______________________________________________ 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.
Hello, I enjoy using R, and find the excellence of this newsgroup removes most of the altitude of the "learning curve". Any learning curve, IMHO, is more than offset by the benefits and capabilities of the language and its awesome plotting tools. A grateful advocate, John Kevin E. Thorpe wrote:> Monica Pisica wrote: > > > > Cons: > > > > - R has a very steep learning curve. > > I don't think the learning curve is any steeper than SAS programming, > it is just a different kind of curve. > > > -- > Kevin E. Thorpe > Biostatistician/Trialist, Knowledge Translation Program > Assistant Professor, Department of Public Health Sciences > Faculty of Medicine, University of Toronto > email: kevin.thorpe at utoronto.ca Tel: 416.864.5776 Fax: 416.864.6057 > > ______________________________________________ > 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.
On the 64-bit part, I tested 2.7.0 on a Dual Core Lenovo ThinkPad and was able to allocate memory beyond 2G. Have not done much else otherwise but it seems to work just fine. H -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Monica Pisica Sent: Thursday, May 22, 2008 9:00 AM To: r-help at r-project.org Subject: [R] Pros and Cons of R Hi, I am doing a very informal presentation for my office about R capabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/OneMapProdWithRGraphics.html together with examples of my own work. I am finishing with pros and cons about R and I am wondering if you can come up with other examples, or comments. Here they are: Pros: - R is a programming environment well suited for statistical analysis. - R is open source and cross platforms (Windows, Mac, Linux). - Fortran, C (C++), and Python wrappers are in place. - Deals well with spatial data, has a robust graphical interface and has an active user group list / forum. - External packages for R are almost daily increasing, most of them based on published up-to-date books and peer-reviewed articles. - R related books - quite a few .... Cons: - R has a very steep learning curve. - There is no perfect "beginner" book. - Experience with other programming languages is a plus / minus. - You can save scripts, but not *.exe. - It is updated several times a year (good) but there are no up-grades. - It seems that it is hard to install correctly under Linux. - Everything you want to do is a command line, minimal GUI. - Memory management problems (depends on your OS), especially when displaying big images at high resolution or working with huge matrices (hundreds of Mb). Also i am wondering if R works under 64 bit computers and if it takes advantage of it. Thanks, Monica _________________________________________________________________ Refresh_family_safety_052008 ______________________________________________ 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.
This is about the 8761st time that this old warhorse has been discussed on this list. I suggest you search the archives (e.g. via CRAN, Gmane, Google,...) for these prior discussions. -- Bert Gunter Genentech P.S. Incidentally, the answer to your question is "It depends..." -- on what your applications/needs are, on what your statistical computing resources are, and most importantly, on what your users are willing to put into using it. Hi, I am doing a very informal presentation for my office about R capabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/O neMapProdWithRGraphics.html together with examples of my own work. I am finishing with pros and cons about R and I am wondering if you can come up with other examples, or comments. Here they are: Pros: - R is a programming environment well suited for statistical analysis. - R is open source and cross platforms (Windows, Mac, Linux). - Fortran, C (C++), and Python wrappers are in place. - Deals well with spatial data, has a robust graphical interface and has an active user group list / forum. - External packages for R are almost daily increasing, most of them based on published up-to-date books and peer-reviewed articles. - R related books - quite a few .. Cons: - R has a very steep learning curve. - There is no perfect "beginner" book. - Experience with other programming languages is a plus / minus. - You can save scripts, but not *.exe. - It is updated several times a year (good) but there are no up-grades. - It seems that it is hard to install correctly under Linux. - Everything you want to do is a command line, minimal GUI. - Memory management problems (depends on your OS), especially when displaying big images at high resolution or working with huge matrices (hundreds of Mb). Also i am wondering if R works under 64 bit computers and if it takes advantage of it. Thanks, Monica _________________________________________________________________ Refresh_family_safety_052008 ______________________________________________ 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.
Charles, I don't consider packages as up-grades, i consider them as enhancements ..... When a new R version is in place you cannot up-grade your old R version, you have to do a new installation and re-load all the packages you used to have and delete / un-install the old version.... of course you can customize how you do this but it is not an up-grade per se as you would go for example from "softname" v.3 to "softname" v.4 using an up-grad einstead of a full installation version. New versions of R are always full versions ..... while this does not bother me a bit since now i have a way of installing everything with very little hassle, it may confuse and even frustrate others less dedicated to using R. So - in my opinion - for a novice in R this might be a "minus". Monica> From: Charles.Annis@StatisticalEngineering.com> To: pisicandru@hotmail.com; r-help@r-project.org> Subject: RE: [R] Pros and Cons of R> Date: Thu, 22 May 2008 12:24:49 -0400> > What do you mean, "there are no up-grades?" There are 1,401 ancillary> packages - all free. That sounds like upgrades to me.> > Of course there is no *perfect* beginner's book, but Peter Dalgaard's> Introductory Statistics with R (Paperback), Springer, 3d printing edition> (January 9, 2004) is pretty close. If you don't know much statistics, it> will teach you statistics while teaching you R. If you already know> statistics, it will demonstrate how to do familiar things using R.> > > Charles Annis, P.E.> > Charles.Annis@StatisticalEngineering.com> phone: 561-352-9699> eFax: 614-455-3265> http://www.StatisticalEngineering.com> > > -----Original Message-----> From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org] On> Behalf Of Monica Pisica> Sent: Thursday, May 22, 2008 12:00 PM> To: r-help@r-project.org> Subject: [R] Pros and Cons of R> > > Hi,> > I am doing a very informal presentation for my office about R capabilities> to deal with and analyze spatial data, display data and maps, and> connections with GIS. I've used in my presentation info from the CRAN, the> spatial Task view, and the more striking graphics examples from> http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS> http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/O> neMapProdWithRGraphics.html together with examples of my own work.> > I am finishing with pros and cons about R and I am wondering if you can come> up with other examples, or comments. Here they are:> > Pros:> > - R is a programming environment well suited for statistical analysis.> - R is open source and cross platforms (Windows, Mac, Linux).> - Fortran, C (C++), and Python wrappers are in place.> - Deals well with spatial data, has a robust graphical interface and has an> active user group list / forum.> - External packages for R are almost daily increasing, most of them based on> published up-to-date books and peer-reviewed articles.> - R related books - quite a few ..> > Cons:> > - R has a very steep learning curve.> - There is no perfect "beginner" book.> - Experience with other programming languages is a plus / minus.> - You can save scripts, but not *.exe.> - It is updated several times a year (good) but there are no up-grades.> - It seems that it is hard to install correctly under Linux.> - Everything you want to do is a command line, minimal GUI.> - Memory management problems (depends on your OS), especially when> displaying big images at high resolution or working with huge matrices> (hundreds of Mb).> > Also i am wondering if R works under 64 bit computers and if it takes> advantage of it.> > Thanks,> > Monica> > _________________________________________________________________> > > Refresh_family_safety_052008> ______________________________________________> 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.> _________________________________________________________________ Change the world with e-mail. Join the i’m Initiative from Microsoft. ld [[alternative HTML version deleted]]
Hi, Monica Pisica wrote: > - There is no perfect ?beginner? book. How about - Crawley, Michael (2007). The R book, Wiley & Sons. - Maindonald, John & John Braun (2007): Data Analysis and Graphics Using R (2nd edition), Cambridge University Press. As a political scientist (with programming experience :) ), both books have helped me to decide in favour of R instead of SPSS when I had to choose the environment for statistical analysis (in Linux). Sadly enough, almost all method books written for social scientists take SPSS as the standard statistical application and, consequently, teach data analysis in a look-for-this-in-SPSS-output-manner. To use R in social sciences, one really must learn how R does things: looking for something in the output is not enough :) BTW, does someone happen to know, if there is any R-book written for social scientists? Kind regards, Kimmo
Hi, IMHO, "- Everything you want to do is a command line, minimal GUI", this should be considered a "Pro". The commandline is much more powerful than a GUI. Cheers, John Monica Pisica wrote:> > Charles, > > I don't consider packages as up-grades, i consider them as enhancements ..... When a new R version is in place you cannot up-grade your old R version, you have to do a new installation and re-load all the packages you used to have and delete / un-install the old version.... of course you can customize how you do this but it is not an up-grade per se as you would go for example from "softname" v.3 to "softname" v.4 using an up-grad einstead of a full installation version. New versions of R are always full versions ..... while this does not bother me a bit since now i have a way of installing everything with very little hassle, it may confuse and even frustrate others less dedicated to using R. So - in my opinion - for a novice in R this might be a "minus". > > Monica> From: Charles.Annis at StatisticalEngineering.com> To: pisicandru at hotmail.com; r-help at r-project.org> Subject: RE: [R] Pros and Cons of R> Date: Thu, 22 May 2008 12:24:49 -0400> > What do you mean, "there are no up-grades?" There are 1,401 ancillary> packages - all free. That sounds like upgrades to me.> > Of course there is no *perfect* beginner's book, but Peter Dalgaard's> Introductory Statistics with R (Paperback), Springer, 3d printing edition> (January 9, 2004) is pretty close. If you don't know much statistics, it> will teach you statistics while teaching you R. If you already know> statistics, it will demonstrate how to do familiar things using R.> > > Charles Annis, P.E.> > Charles.Annis at StatisticalEngineering.com> phone: 561-352-9699> eFax: 614-455-3265> http://www.StatisticalEngineering.com> > > -----Original Message-----> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On> Behalf Of Monica Pisica> Sent: Thursday, May 22, 2008 12:00 !PM> To: r-help at r-project.org> Subject: [R] Pros and Cons of R> > > Hi,> > I am doing a very informal presentation for my office about R capabilities> to deal with and analyze spatial data, display data and maps, and> connections with GIS. I've used in my presentation info from the CRAN, the> spatial Task view, and the more striking graphics examples from> http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS> http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/O> neMapProdWithRGraphics.html together with examples of my own work.> > I am finishing with pros and cons about R and I am wondering if you can come> up with other examples, or comments. Here they are:> > Pros:> > - R is a programming environment well suited for statistical analysis.> - R is open source and cross platforms (Windows, Mac, Linux).> - Fortran, C (C++), and Python wrappers are in place.> - Deals well with spatial data, has a robust graphical interface and has an> active user g! roup list / forum.> - External packages for R are almost daily! increasing, most of them based on> published up-to-date books and peer-reviewed articles.> - R related books - quite a few ..> > Cons:> > - R has a very steep learning curve.> - There is no perfect "beginner" book.> - Experience with other programming languages is a plus / minus.> - You can save scripts, but not *.exe.> - It is updated several times a year (good) but there are no up-grades.> - It seems that it is hard to install correctly under Linux.> - Everything you want to do is a command line, minimal GUI.> - Memory management problems (depends on your OS), especially when> displaying big images at high resolution or working with huge matrices> (hundreds of Mb).> > Also i am wondering if R works under 64 bit computers and if it takes> advantage of it.> > Thanks,> > Monica> > _________________________________________________________________> > > Refresh_family_safety_052008> ______________________________________________> 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.>> _________________________________________________________________ > Change the world with e-mail. Join the i?m Initiative from Microsoft. > > ld > [[alternative HTML version deleted]]
On Thu, May 22, 2008 at 12:00 PM, Monica Pisica <pisicandru at hotmail.com> wrote:> > Hi, > > I am doing a very informal presentation for my office about R capabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/OneMapProdWithRGraphics.html together with examples of my own work. > > I am finishing with pros and cons about R and I am wondering if you can come up with other examples, or comments. Here they are: > > Pros: > > - R is a programming environment well suited for statistical analysis. > - R is open source and cross platforms (Windows, Mac, Linux). > - Fortran, C (C++), and Python wrappers are in place. > - Deals well with spatial data, has a robust graphical interface and has an active user group list / forum. > - External packages for R are almost daily increasing, most of them based on published up-to-date books and peer-reviewed articles. > - R related books ? quite a few ?. > > Cons: > > - R has a very steep learning curve. > - There is no perfect "beginner" book.I don't think that there can be the perfect book since different people have different backgrounds and different interests and that implies a different book for different people; however, there are many books and there is a large amount of material available: http://cran.r-project.org/other-docs.html http://www.r-project.org/doc/bib/R-publications.html http://cran.r-project.org/manuals.html and vignettes in individual packages.> - Experience with other programming languages is a plus / minus. > - You can save scripts, but not *.exe. > - It is updated several times a year (good) but there are no up-grades.What's the difference bewteen an update and an up-grade? If you mean addon packages there are 1500+ in CRAN and BioC.> - It seems that it is hard to install correctly under Linux. > - Everything you want to do is a command line, minimal GUI.There do exist GUI front ends although the full power of R requires the command line: http://www.sciviews.org/_rgui/ Also its possible to write your own GUI front ends to your own programs.> - Memory management problems (depends on your OS), especially when displaying big images at high resolution or working with huge matrices (hundreds of Mb). > > Also i am wondering if R works under 64 bit computers and if it takes advantage of it. > > Thanks, > > Monica > > _________________________________________________________________ > > > Refresh_family_safety_052008 > ______________________________________________ > 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. >
Monica Pisica wrote:> - You can save scripts, but not *.exe.If you want to contrast R with statistical packages like SPSS or Stata (and if your audience has rather a background in those than in general purpose languages), I think this is not really a problem unless I missed something recently about the capabilities of SPSS or Stata. Best, Roland
Monica, here are some other Pros to consider about R: 1) IMHO, the most important reason for using R is that expressed by John Chambers as the aim of the S language: "to turn ideas into software, quickly and faithfully." The broad capabilities of R facilitate the integration of data maintenance and cleaning, exploratory data analysis, model estimation, model implementation, model calibration, model application, and the reporting and display of model outputs. This has tremendous productivity advantages. For example, I was able to meet a tight timeline for developing a regional land use model because R allowed me to easily move through the steps of model development from data analysis to implementation. I even found that I could do some geographical operations that could not be done using our GIS software. In addition, all of the model outputs (including a very many maps) were produced with R. Once you learn how to use R in this way, you will find it takes less time to program the outputs in R than to produce them in GIS. R yields productivity advantages in smaller ways too. We've developed a number of small applications to solve GIS or other problems that could not be solved as easily using other tools. Moreover, once they have been solved using R, the solutions are easily automated or recycled in other contexts. 2) R facilitates documentation and replication. Previous to using R, we did our data analysis and implemented our models in a variety of platforms. For example, Access, Excel, SPSS and Stata were all previously used in household survey data processing and analysis. This was a documentation nightmare. All the steps can be done using R instead and documentation can be easily included in the scripts. If care is taken to use good naming conventions that emphasize readability, the scripts can be largely self documenting. This also facilitates group work. Since we started using R in our work, we have been able to greatly increase our modeling capabilities and output with no increase in staffing. Brian Gregor, P.E. Senior Transportation Analyst Oregon Department of Transportation Transportation Planning Analysis Unit 555 13th Street NE Salem, OR 97301 503-986-4120>Message: 22 >Date: Thu, 22 May 2008 16:00:10 +0000 >From: Monica Pisica <pisicandru at hotmail.com> >Subject: [R] Pros and Cons of R >To: <r-help at r-project.org> >Message-ID: <BAY104-W52F35E50A680C814F52417C3C60 at phx.gbl> >Content-Type: text/plain; charset="Windows-1252" > > >Hi, > >I am doing a very informal presentation for my office about Rcapabilities to deal with and analyze spatial data, display data and maps, and connections with GIS. I've used in my presentation info from the CRAN, the spatial Task view, and the more striking graphics examples from http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphi cs/OneMapProdWithRGraphics.html together with examples of my own work.> >I am finishing with pros and cons about R and I am wondering if you cancome up with other examples, or comments. Here they are:> >Pros: > >- R is a programming environment well suited for statistical analysis. >- R is open source and cross platforms (Windows, Mac, Linux). >- Fortran, C (C++), and Python wrappers are in place. >- Deals well with spatial data, has a robust graphical interface andhas an active user group list / forum.>- External packages for R are almost daily increasing, most of thembased on published up-to-date books and peer-reviewed articles.>- R related books ? quite a few ?. > >Cons: > >- R has a very steep learning curve. >- There is no perfect ?beginner? book. >- Experience with other programming languages is a plus / minus. >- You can save scripts, but not *.exe. >- It is updated several times a year (good) but there are no up-grades. >- It seems that it is hard to install correctly under Linux. >- Everything you want to do is a command line, minimal GUI. >- Memory management problems (depends on your OS), especially whendisplaying big images at high resolution or working with huge matrices (hundreds of Mb).> >Also i am wondering if R works under 64 bit computers and if it takesadvantage of it.> >Thanks, > >Monica
I think one significant problem is the lack of 3D graphics support with interactivity as per MATLAB ( I here Xgobi offers something hear but I couldn't comment having not used it) On the GUI issue, I'm split - once you get used to R then it's great just to use the command line - but as a language for teaching students (especially those outside statistics - E.g. social sciences) a command like can be quite daunting. R-Commander I guess addresses this to some degree - though it's no match for the GUI offered by S-Plus (in my opinion). I don't think a working knowledge of any other language can be considered a negative - any half decent programmer should be able to pick up new languages fairly quickly if they are experienced with one. Previous experience is especially useful if moving from matrix style language to R (E.g. MATLAB / OCTAVE). I think your comments on "hard to install on linux" is a fair one -- in terms of installing the base system that's fine, but when it comes to install packages, I still get tripped up on compilation problems (I just posted a topic on one such problem). It is certainly harder than say installing a MATLAB tool box. Cheers David Monica Pisica wrote:> > > Hi, > > I am doing a very informal presentation for my office about R capabilities > to deal with and analyze spatial data, display data and maps, and > connections with GIS. I've used in my presentation info from the CRAN, the > spatial Task view, and the more striking graphics examples from > http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS > http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/OneMapProdWithRGraphics.html > together with examples of my own work. > > I am finishing with pros and cons about R and I am wondering if you can > come up with other examples, or comments. Here they are: > > Pros: > > - R is a programming environment well suited for statistical analysis. > - R is open source and cross platforms (Windows, Mac, Linux). > - Fortran, C (C++), and Python wrappers are in place. > - Deals well with spatial data, has a robust graphical interface and has > an active user group list / forum. > - External packages for R are almost daily increasing, most of them based > on published up-to-date books and peer-reviewed articles. > - R related books ? quite a few ?. > > Cons: > > - R has a very steep learning curve. > - There is no perfect ?beginner? book. > - Experience with other programming languages is a plus / minus. > - You can save scripts, but not *.exe. > - It is updated several times a year (good) but there are no up-grades. > - It seems that it is hard to install correctly under Linux. > - Everything you want to do is a command line, minimal GUI. > - Memory management problems (depends on your OS), especially when > displaying big images at high resolution or working with huge matrices > (hundreds of Mb). > > Also i am wondering if R works under 64 bit computers and if it takes > advantage of it. > > Thanks, > > Monica > > _________________________________________________________________ > > > Refresh_family_safety_052008 > ______________________________________________ > 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. > >-- View this message in context: http://www.nabble.com/Pros-and-Cons-of-R-tp17407521p17450128.html Sent from the R help mailing list archive at Nabble.com.
R is definitely an excellent environment for data analysis and display. It has quickly become the tool that I use to bind together different models and process the resulting data into reports and graphics. The Sweave package can be especially useful for accomplishing this. R has also been integrated into some GIS environments, the GRASS system is a good example of this. The book "Open Source GIS: A GRASS GIS Approach" by M.Netler and H. Mitasova. provides an overview of this capability. The following post in the QGIS blog also shows how R can be used to output data as shapefiles which can then be loaded into a GIS application: http://blog.qgis.org/node/112 Monica Pisica wrote:> > > Cons: > > - R has a very steep learning curve. > >Based on my my experience conducting data analysis and visualization using Fortran and MATLAB, R was refreshingly easy to learn. The demo() and example() functions provide tremendous insight into the use of different tools in R by executing code and showing the results. I also found it extremely easy to obtain consistent graphical output from R. Producing standardized views of different datasets in MATLAB can be an exercise in frustration compared to what I am able to achieve using R. -- View this message in context: http://www.nabble.com/Pros-and-Cons-of-R-tp17407521p17451695.html Sent from the R help mailing list archive at Nabble.com.
K. Elo wrote:> Hi, > > Monica Pisica wrote: > > - There is no perfect ?beginner? book. > > How about > - Crawley, Michael (2007). The R book, Wiley & Sons. > - Maindonald, John & John Braun (2007): Data Analysis and Graphics Using > R (2nd edition), Cambridge University Press. > > As a political scientist (with programming experience :) ), both books > have helped me to decide in favour of R instead of SPSS when I had to > choose the environment for statistical analysis (in Linux). Sadly > enough, almost all method books written for social scientists take SPSS > as the standard statistical application and, consequently, teach data > analysis in a look-for-this-in-SPSS-output-manner. To use R in social > sciences, one really must learn how R does things: looking for something > in the output is not enough :) > > BTW, does someone happen to know, if there is any R-book written for > social scientists? > > Kind regards, > Kimmo >Some of the "Quantitative Applications in the Social Sciences" series of monographs by SAGE publications use R (such as "Spatial Regression Models") and there are a few Econometrics books out there (Econometrics in R by Grant Farnsworth is available for free in the contributed section of the CRAN website).