Re: [R] what is the .Machine$double.xmin for a 64 bit machine?

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Tue 12 Jul 2005 - 21:07:53 EST

It's a floating-point quantity: `64 bit' refers to the pointer size (only).

Almost all current R platforms use IEC60559 arithmetic for real numbers and 32-bit integers for integers, so differ only in the way the compiler orders operations and stores to memory (thereby losing precision on some CPUs).

On Tue, 12 Jul 2005, S.O. Nyangoma wrote:

>
> I use a 32 bit machine. For those using 64 bit machines,
>
> what is the .Machine$double.xmin for for machines?
>
> regards. Stephen.
>
>
>
>
> ----- Original Message -----
> From: Achim Zeileis <Achim.Zeileis@wu-wien.ac.at>
> Date: Tuesday, July 12, 2005 10:51 am
> Subject: Re: [R] exact values for p-values - more information.
>
>> On Tue, 12 Jul 2005, S.O. Nyangoma wrote:
>>
>>>> If they have the same degrees of freedom, use the test statistic
>>>> and not
>>>> the p value for comparing them.
>>>> Z
>>>
>>> I appretiate your input to this discussion. Do you know of a
>> reference> to your statement above?
>>
>> ?? Any basic statistics book? Distribution functions tend to be
>> monotonous.
>>
>>> I had actually used the test-statistic which in my case is r-
> squared
>>> to compare them. This is in my view was adequate but I also
>> think it
>>> is more convincing to say something about the p-values
>>
>> Not really `more' convincing, it's all pretty equivalent when the
>> numberof estimated parameters is the same. You can also compare
>> the fitted
>> models via their associated residual sum of squares which I would
> find
>> most intuitive because that is the objective function you are
>> trying to
>> minimize via OLS.
>> Z
>>
>>> (difficulties
>>> in computing them, and hence the rationale of solely using the
>> test-
>>> stat).
>>>
>>> regards. Stephen.
>>>
>>>
>>>
>>
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
>

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
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@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Received on Tue Jul 12 21:10:50 2005

This archive was generated by hypermail 2.1.8 : Fri 03 Mar 2006 - 03:33:32 EST