Thanks! The "get / assign" combination does just what I want, and the warning about the pre-existence of .Random.seed was very helpful. As for set.seed, I have used it to create a replicable state (in fact, I have an option to use it in the function I was writing that prompted my query), but I didn't see any indication that it could be used to restore a state for which you don't necessarily know the seed.
I got a couple of good offlist responses, too. One person told me about the "<<-" assignment operator (with an admonishment to use it judiciously). Another responder mentioned the setRNG package, which has a specific methodology for saving the random number generator state. -- TMK -- 212-460-5430 home 917-656-5351 cell >From: Prof Brian Ripley <[EMAIL PROTECTED]> >To: Talbot Katz <[EMAIL PROTECTED]> >CC: r-help@stat.math.ethz.ch >Subject: Re: [R] Restoring .Random.seed >Date: Thu, 31 May 2007 20:57:09 +0100 (BST) > >On Thu, 31 May 2007, Talbot Katz wrote: > >>Hi. >> >>Suppose I have a function which does some random number generation within. >>The random number generation inside the function changes the value of >>.Random.seed in the calling environment. If I want to restore the > ^^^^^^^^^^^^^^^^^^^^^^^^^^ >That is your misunderstanding. From the help page > > The object '.Random.seed' is only looked for in the user's > workspace. > >which seems plain enough. So, you can do > >save.seed <- get(".Random.seed", .GlobalEnv) >assign(".Randon.seed", save.seed, .GlobalEnv) > >to save and restore, *provided* that random numbers have been used in the >session (or .Random.seed will not exist). > >However, the help recommends using set.seed(), and why not follow the >advice? > >>pre-function call .Random.seed, I can do: >> >>save.seed<-.Random.seed >>result<-myfunction() >>.Random.seed<-save.seed >> >>Is there a way to do the restoration inside the function? I tried putting >>the "save.seed<-.Random.seed" and ".Random.seed<-save.seed" statements >>inside the function, but that didn't work. > >As documented on the help page. > >[...] > >-- >Brian D. Ripley, [EMAIL PROTECTED] >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 and provide commented, minimal, self-contained, reproducible code.