Thanks to All, The comments were very helpful; however, the the simulation is running very slow. I reduced the number of loops (conditions) so I have 36 loops, and the data-generation occurs 1000 times within each loop. At the end of each 1000 reps, I saved the summary (e.g., mean) of the reps to a single row vector, and then saved it in a "fileshare" database. When the simulation is finished, I rbind() the 36 rows of the database objects into a final simulation result.
Thanks again, Davood Tofighi On Wed, Mar 5, 2008 at 8:44 AM, Paul Gilbert <[EMAIL PROTECTED]> wrote: > Davood Tofighi wrote: > > Thanks for your reply. For each condition, I will have a matrix or data > > frames of 1000 rows and 4 columns. I also have a total of 64 conditions > for > > now. So, in total, I will have 64 matrices or data frames of 1000 rows > and 4 > > columns. The format of data I would like to store would be data frames > or > > matrices. I also would like to store the data for later use, > I generally find it is better to store the seed and other data you need > to reproduce the experiment, rather than trying to store the data (see, > for example, package setRNG). If you save only the summary statistics > you need, then you can usually do it in memory. (Be sure to assign > variables for the statistics to their full size first and then populate > them, rather than extending them at each step.) If you write things to > files then it will slow down your simulation a lot. In fact, in most > cases it will be quicker to re-run the experiment than it will be to > read the data from disk. > > Paul > > e.g., a plot of > > the empirical distribution of the chi^2, or to compute the power of > Chi^2 > > across 1000 reps for each condition. > > > > On Mon, Mar 3, 2008 at 7:03 PM, jim holtman <[EMAIL PROTECTED]> wrote: > > > > > >> What is the format of the data you are storing (single value, > >> multivalued vector, matrix, dataframe, ...)? This will help formulate > >> a solution. What do you plan to do with the data? Are you going to > >> do further analysis, write it to flat files, store it in a data base, > >> etc.? How big are the data objects you are manipulating? > >> > >> On Mon, Mar 3, 2008 at 7:05 PM, Davood Tofighi <[EMAIL PROTECTED]> > wrote: > >> > >>> Dear All, > >>> > >>> I am running a Monte Carlo simulation study and have some questions on > >>> > >> how > >> > >>> to manage data storage efficiently at the end of each 1000 replication > >>> > >> loop. > >> > >>> I have three conditions coded using the FOR {} loops and a FOR loop > that > >>> generates data for each condition, performs analysis, and computes a > >>> statistic 1000 times. Therefore, for each condition, I will have 1000 > >>> statistic values. My question is what's the best way to store the 1000 > >>> statistic for each condition. Any suggestion on how to manage such > >>> simulation studies is greatly appreciated. > >>> Thanks, > >>> > >>> -- > >>> Davood Tofighi > >>> Department of Psychology > >>> Arizona State University > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> ______________________________________________ > >>> 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. > >>> > >>> > >> > >> -- > >> Jim Holtman > >> Cincinnati, OH > >> +1 513 646 9390 > >> > >> What is the problem you are trying to solve? > >> > >> > > > > > > > > > > ==================================================================================== > > La version française suit le texte anglais. > > > ------------------------------------------------------------------------------------ > > This email may contain privileged and/or confidential information, and the > Bank of > Canada does not waive any related rights. Any distribution, use, or > copying of this > email or the information it contains by other than the intended recipient > is > unauthorized. If you received this email in error please delete it > immediately from > your system and notify the sender promptly by email that you have done so. > > > ------------------------------------------------------------------------------------ > > Le présent courriel peut contenir de l'information privilégiée ou > confidentielle. > La Banque du Canada ne renonce pas aux droits qui s'y rapportent. Toute > diffusion, > utilisation ou copie de ce courriel ou des renseignements qu'il contient > par une > personne autre que le ou les destinataires désignés est interdite. Si vous > recevez > ce courriel par erreur, veuillez le supprimer immédiatement et envoyer > sans délai à > l'expéditeur un message électronique pour l'aviser que vous avez éliminé > de votre > ordinateur toute copie du courriel reçu. > -- Davood Tofighi Department of Psychology Arizona State University P.O. BOX 871104 Tempe, AZ 85287-1104 Tel.:480-727-7884 [[alternative HTML version deleted]]
______________________________________________ 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.