On Mon, Sep 8, 2008 at 7:47 PM, Dimitri Liakhovitski <[EMAIL PROTECTED]> wrote:
> Thank you everyone for your responses. I'll answer several questions.
>
> 1. > Disclaimer: I have **NO IDEA** of the details of what you want
> to do or why
>> -- but I am willing to bet that there are better ways of
Hi Dimitri,
On Mon, 8 Sep 2008, Dimitri Liakhovitski wrote:
Dear R-list,
maybe some of you could point me in the right direction:
Are you aware of any FREE Fortran or Java libraries/actual pieces of
code that are VERY efficient (time-wise) in running the regular linear
least-squares multiple r
Thanks a lot, everybody!
On Mon, Sep 8, 2008 at 3:11 PM, Lucke, Joseph F
<[EMAIL PROTECTED]> wrote:
> Although I along with the other believe there probably is an efficient R
> solution, the answer to your direct question can perhaps be found at
> http://www.fortran.com/. The free GNU G95 fortra
Although I along with the other believe there probably is an efficient R
solution, the answer to your direct question can perhaps be found at
http://www.fortran.com/. The free GNU G95 fortran compiler is at
http://www.g95.org/
Joe
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL
the squares of the residuals.
>>
>>>
>>> 3. I know that for similarly challenging situations people did used
>>> Fortran compilers. So, anyone heard of a free Fortran library or an
>>> efficient piece of code?
>>>
>>> Thank you!
>>> Dim
uals.
>
>>
>> 3. I know that for similarly challenging situations people did used
>> Fortran compilers. So, anyone heard of a free Fortran library or an
>> efficient piece of code?
>>
>> Thank you!
>> Dimitri
>>
>>
>>>
>>> -
ary or an
> efficient piece of code?
>
> Thank you!
> Dimitri
>
>
>>
>> -- Bert Gunter
>>
>> -Original Message-
>> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
>> Behalf Of Dimitri Liakhovitski
>> Sent: Monday, September 08, 2008
To: Prof Brian Ripley
> Cc: R-Help List
> Subject: Re: [R] Question about multiple regression
>
> Yes, see my previous e-mail on how long R takes (270 seconds for one
> of the 1,800,000 sets I need) - using system.time.
> Not sure how to test the same for Fortran...
>
>
Try:
sum(lm.fit(x, y)$residuals^2)
On Mon, Sep 8, 2008 at 12:52 PM, Dimitri Liakhovitski <[EMAIL PROTECTED]> wrote:
> Thank you for reminding me, Gabor. I forgot to mention: So far, I have
> run one test set of regressions using lm. It took R 270 sec. I need to
> run 1,800,000 of those, which wou
e: [R] Question about multiple regression
Yes, see my previous e-mail on how long R takes (270 seconds for one
of the 1,800,000 sets I need) - using system.time.
Not sure how to test the same for Fortran...
On Mon, Sep 8, 2008 at 12:51 PM, Prof Brian Ripley
<[EMAIL PROTECTED]> wrote:
> Are you
Yes, see my previous e-mail on how long R takes (270 seconds for one
of the 1,800,000 sets I need) - using system.time.
Not sure how to test the same for Fortran...
On Mon, Sep 8, 2008 at 12:51 PM, Prof Brian Ripley
<[EMAIL PROTECTED]> wrote:
> Are you sure R's ways are not fast enough (there are
Thank you for reminding me, Gabor. I forgot to mention: So far, I have
run one test set of regressions using lm. It took R 270 sec. I need to
run 1,800,000 of those, which would imply 15.4 years of computing time
:)
I have not done the same for lm.fit because I am not sure how to get
model R squar
Are you sure R's ways are not fast enough (there are many layers
underneath lm)? For an example of how you might do this at C/Fortran
level, see the function lqs() in MASS.
On Mon, 8 Sep 2008, Dimitri Liakhovitski wrote:
Dear R-list,
maybe some of you could point me in the right direction:
I would test the speed before making such as assumption. Note that
lm.fit is faster than lm and if they have the same x matrix then
you can do many in one call by having y be a matrix.
On Mon, Sep 8, 2008 at 12:05 PM, Dimitri Liakhovitski <[EMAIL PROTECTED]> wrote:
> Dear R-list,
> maybe some of
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