To improve the memory limitation impeding R, I found the package
SOAR very useful:
http://cran.r-project.org/web/packages/SOAR/vignettes/SOAR.pdf
Thank you
M. Ndiaye
From:
amelia-bounces@lists.gking.harvard.edu
[mailto:amelia-bounces@lists.gking.harvard.edu] On Behalf Of Matt
Blackwell
Sent: Thursday, February 07, 2013 11:24 AM
To: OMER FARUK Orsun
Cc: amelia@lists.gking.harvard.edu
Subject: Re: [amelia] Error of " resulting vector exceeds vector
length limit in 'AnswerType'"
Hi Ömer,
First,
note that you may not have enough observations to get good
imputations with that many variables. Amelia might have poor properties in that
case. You can save a lot of hassle here by not interacting the polynomials of
time with the cross-section (setting "intercs = FALSE").
I imagine you
have 500 GB of hard disk space, not RAM, but either way, this is probably
related to the maximum vector size that R can handle, which is currently
2^31-1. Obviously that is *very* large, but if you want to go beyond that you
would have to use R 3.0.0 (still under development) which will allow for
longer vectors on certain machines. For more information, see this
help file in R:
?"Memory-limits"
If you are on
Windows, you might be able to increase the amount of memory dedicated the R
process.
Hope that helps!
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Political Science
University of Rochester
On Thu, Feb 7, 2013 at 12:10 PM, OMER FARUK Orsun <oorsun@ku.edu.tr> wrote:
Hi Matt,
Many thanks for your response. The missingness in my data is
severe, as a result, I might need to introduce all available data. Is there
another way to avoid memory related errors given that I have a 500 GB RAM
computer?
Best Regards,
Ömer
_________________________________
Ömer Faruk
Örsün
PhD Candidate
Department of
International Relations
Koç University
CAS 289
_________________________________
On Thu, Feb 7, 2013 at 4:54 PM, Matt Blackwell <m.blackwell@rochester.edu>
wrote:
Hi Ömer,
It seems as though you are running into memory issues with R
itself. Note that using "intercs = TRUE" and "polytime = 2"
will add 3*K variables to the data, where K is the number of dyads in the data.
Given your description of the data, that could be an extremely large data set.
You might want to run Amelia on a smaller subset of the data to see how the
imputations go and then tentatively test out smaller imputation models.
Hope that helps!
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Political Science
University of Rochester
On Thu, Feb 7, 2013 at 7:24 AM, OMER FARUK Orsun <oorsun@ku.edu.tr> wrote: