[R] Moving to Mac OS X

[Noah Silverman]

Thanks Steve,

That's a big help.



On 9/11/09 12:48 PM, Steve Lianoglou wrote:
> Hi,
>
> On Sep 11, 2009, at 3:40 PM, Noah Silverman wrote:
>
>> Steve,
>>
>> You make a good point.  I confused 64 bit with a multi-core setup.
>>
>> That said, I don't belive the pretty packaged up GUI has a 64 bit 
>> version, just the "raw terminal" version does.
>
> There is a 64bit version of the R.app GUI, you can get it from here:
>
> http://r.research.att.com/#GUI
>
> For some reason the 2.9-leopard.dmg is missing (though the 2.10-devel 
> is there). This was just noticed on R-sig-mac earlier today and, 
> AFAIK, it should be back soon.
>
> -steve
>
>>
>>
>>
>> On 9/11/09 12:38 PM, Steve Lianoglou wrote:
>>> Hi,
>>>
>>> On Sep 11, 2009, at 3:08 PM, Noah Silverman wrote:
>>>> 3) I purposefully chose NOT to install 64bit R.  I have a dual-core 
>>>> machine.  With the 32 bit version, R will happily keep one core 
>>>> running at 100%, but then I have other core free for my "regular" 
>>>> work.
>>>
>>> Using 64bit R shouldn't change your CPU usage, so if you want to use 
>>> it to deal with larger data, feel free to do so ... unless you 
>>> explicitly write code to use >1 cpu, you'll still have another cpu 
>>> free to do with what you will (assuming you have enough ram).
>>>
>>> -steve
>>>
>>>> On 9/11/09 10:32 AM, Marc Schwartz wrote:
>>>>> On Sep 11, 2009, at 12:15 PM, Victor Manuel Garcia Guerrero wrote:
>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> I have been using R on Windows for a long time, but now I am 
>>>>>> ready to move to Mac OS X, but I was just wondering if R works 
>>>>>> better on Mac than on Windows. This is because I had some memory 
>>>>>> size issues in the past.
>>>>>>
>>>>>> Another question is if some of you know an R editor for Mac (just 
>>>>>> like Tinn-R).
>>>>>>
>>>>>> Thanks.
>>>>>
>>>>> The notion of "better" is always in the eyes of the useR and will 
>>>>> depend upon specific criteria.
>>>>>
>>>>> OSX can run R in both 32 bit and 64 bit modes and indeed the 
>>>>> default OSX download for R provided by Simon installs and supports 
>>>>> both. If you use the 32 bit version, then from a memory management 
>>>>> standpoint, you will not see demonstrable gains over Windows. 
>>>>> However, with the 64 bit version, you will avail yourself of a 
>>>>> much larger memory address space as compared to running 32 bit R 
>>>>> on Windows. That of course presumes that you have a lot of RAM in 
>>>>> your Mac to actually take advantage of the larger address space.
>>>>>
>>>>> The 64 bit memory address space is also available via Linux, with 
>>>>> appropriate hardware.
>>>>>
>>>>>
>>>>> You might want to review the R OSX FAQ:
>>>>>
>>>>> http://cran.r-project.org/bin/macosx/RMacOSX-FAQ.html
>>>>>
>>>>> and also note that there is a OSX specific e-mail list:
>>>>>
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mac
>>>>>
>>>>>
>>>>> As far as editors, I am not familiar with the details of Tinn-R, 
>>>>> but ESS/Emacs is available for OSX and this is what I use 
>>>>> (continuing what I had been using on Linux for the past number of 
>>>>> years).  Others will likely be able to provide other 
>>>>> recommendations and you might want to search the R-SIG-Mac list 
>>>>> archives as no doubt there have been such discussions in the past.
>>>>>
>>>>> HTH,
>>>>>
>>>>> Marc Schwartz
>>>>>
>>>>> ______________________________________________
>>>>> 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.
>>>>
>>>> ______________________________________________
>>>> 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.
>>>
>>> -- 
>>> Steve Lianoglou
>>> Graduate Student: Computational Systems Biology
>>>  |  Memorial Sloan-Kettering Cancer Center
>>>  |  Weill Medical College of Cornell University
>>> Contact Info: http://cbio.mskcc.org/~lianos/contact
>>>
>>
>> ______________________________________________
>> 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.
>
> -- 
> Steve Lianoglou
> Graduate Student: Computational Systems Biology
>   |  Memorial Sloan-Kettering Cancer Center
>   |  Weill Medical College of Cornell University
> Contact Info: http://cbio.mskcc.org/~lianos/contact
>