On Thu, 14 Feb 2008, [EMAIL PROTECTED] wrote: > Dear Prof Ripley and Don, > > Thank you all for your kind reply. > > The UNIX system we have is Sparc Solaris v8 (a 64bit version). The > Precompiled binary distributions of the base system and contributed packages > are only available for Linux, MacOS X and Windows. The only thing available > for UNIX seems Source Code for all Platforms. Could you please guide me to > the "Prebuilt versions of R are available for Solaris" and the Solaris > binary?
There are binaries for that too, as mentioned in the manual. I don't know why I have to read the manual for you, but see http://www.sunfreeware.com/indexintel8.html. They have R 2.6.0. > By the way, given the UNIX system is pretty old (Solaris v8), could the > latest version of R be installed on such old system or we have to install an > earlier version of R? R 2.6.2 will install from the sources. > Thanks a lot in advance. > > Regards, > Jin > > -----Original Message----- > From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] > Sent: Tuesday, 12 February 2008 5:06 > To: Li Jin > Cc: r-help@r-project.org > Subject: Re: [R] Linux, UNIX, XP32, Vista X64 or ...? [SEC=UNCLASSIFIED] > > On Tue, 12 Feb 2008, [EMAIL PROTECTED] wrote: > >> Thanks to all for your kind suggestions. >> >> After some discussion with our IT staff, I was told the UNIX system we have >> is Solaris and installation of R is very time consuming because "Given that >> this software is not standard, and given the amount of time required to >> compile the software (and potentially it's dependencies), it will need to > be >> resourced as a project ..." From my experience with IT staff, it may take >> quite a long time for them to set up such project, let alone the >> installation. > > Prebuilt versions of R are available for Solaris -- and the 'R > Installation and Administration' manual told them so. > >> Given that, I wonder if it is possible to install it myself. As I have >> mentioned before, I have no experience in using UNIX, but I will have an >> access to the UNIX system soon. Any suggestions and help are greatly >> appreciated. > > It is easy to install R from the sources if you have the compilers and > e.g. Tcl/Tk installed. But a Solaris box quite possibly does not, and > then a binary install is much easier. > >> >> Regards, >> Jin >> >> -----Original Message----- >> From: Gabor Grothendieck [mailto:[EMAIL PROTECTED] >> Sent: Monday, 28 January 2008 11:38 >> To: Li Jin >> Cc: r-help@r-project.org >> Subject: Re: [R] Linux, UNIX, XP32, Vista X64 or ...? [SEC=UNCLASSIFIED] >> >> On the PC there is a builtin GUI but not on UNIX and there are >> some packages that are OS specific in which case you might >> get more or less selection but probably more. Also depending >> on the specific system you may have greater difficulty installing >> certain packages due to the need to compile them on UNIX >> and the possibility exists that you don't quite have the right >> libraries. On Windows you get binaries so this is not a problem. >> I have repeatedly found that common packages that I took >> for granted on Windows had some problem with installation >> on UNIX and I had to hunt around and figure out what the problem >> was with my UNIDX libraries or possibly some other problem. >> For all R packages this won't be a problem but for packages >> that use C and FORTRAN this can be. Although I am lumping >> all UNIX systems together I think this varies quite a bit from >> one particular type/distro of UNIX/Linux to another and I suspect if you >> are careful in picking out the right one (if you have a choice) you >> will actually have zero problems. >> >> On Jan 23, 2008 6:08 PM, <[EMAIL PROTECTED]> wrote: >>> Dear All, >>> I am currently using R in Windows PC with a 2 GB of RAM. Some pretty large >>> datasets are expected soon, perhaps in an order of several GB. I am facing >> a >>> similar situation like Ralph, either to get a new PC with a bigger RAM or >>> else. I am just wondering if R is getting faster in other systems like > UNIX >>> or Linux. Any suggestions are appreciated. >>> Regards, >>> Jin >>> -------------------------------------------- >>> Jin Li, PhD >>> Spatial Modeller/ >>> Computational Statistician >>> Marine & Coastal Environment >>> Geoscience Australia >>> Ph: 61 (02) 6249 9899 >>> Fax: 61 (02) 6249 9956 >>> email: [EMAIL PROTECTED] >>> -------------------------------------------- >>> >>> >>> -----Original Message----- >>> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > On >>> Behalf Of Prof Brian Ripley >>> Sent: Thursday, 24 January 2008 12:05 >>> To: Ralph79 >>> Cc: r-help@r-project.org >>> Subject: Re: [R] Problems with XP32-"3GB-patch"?/ Worth upgrading to Vista >>> X64? >>> >>> On Wed, 23 Jan 2008, Ralph79 wrote: >>> >>>> >>>> Dear R-Users, >>>> >>>> as I will start a huge simulation in a few weeks, I am about to buy a new >>>> and fast PC. I have noticed, that the RAM has been the limiting factor in >>>> many of my calculations up to now (I had 2 GB in my "old" system, but >>>> Windows still used quite a lot of virtual memory), hence my new computer >>>> will have 4 GB of fast DDR2-800 RAM. >>>> >>>> However, I know that 1.) Windows 32 bit cannot make use of more than >> about >>>> 3,2 GB RAM and 2.) it is normally not allowed to allocate more than 2 GB >> of >>>> RAM to one single application (at least under XP, I don't know if that >> has >>>> changed under Vista?). >>>> >>>> I remember from the R-FAQ that you can manually adjust XP so that it >>>> allocates up to 3 GB to one application ("the 3GB patch"), but I read in >> a >>>> PC-magazine and some message boards that this may cause problems. Does >>>> anybody of you successfully use this "trick" without any problems? >>> >>> Yes, many people: most 32-bit Exchange servers use it. Please don't rate >>> the advice in the R documentation below tittle-tattle you read on the web. >>> >>>> Would it be wise to use a 64bit OS, as e.g. Vista X64? I think, under >> Vista >>>> X64 it should be no problem to allocate 4 GB of RAM to R. Any experiences >>>> with that? >>> >>> That's what the rw-FAQ says, and we do write answers based on experience! >>> >>>> Thanks in advance, >>>> Ralph Wirth >>>> >>>> >>>> ----- >>>> Ralph Wirth >>>> University Erlangen-Nuremberg, Chair of Statistics >>>> GfK Group, Department of Methods and Product Development >>>> >>>> >>> >>> -- >>> Brian D. Ripley, [EMAIL PROTECTED] >>> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ >>> University of Oxford, Tel: +44 1865 272861 (self) >>> 1 South Parks Road, +44 1865 272866 (PA) >>> Oxford OX1 3TG, UK Fax: +44 1865 272595 >>> >>> ______________________________________________ >>> 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. >>> >>> ______________________________________________ >>> 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. >>> >> >> ______________________________________________ >> 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. >> > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ 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.