I'm writing to ask for a policy exception, or advice on how to make this package CRAN allowable.
http://rweb.quant.ku.edu/kran/src/contrib/portableParallelSeeds_0.9.tar.gz Yesterday I tried to submit a package on CRAN and Dr Ripley pointed out that I had not understood the instructions about packages. Here's the part where the R check gives a Note * checking R code for possible problems ... NOTE Found the following assignments to the global environment: File ‘portableParallelSeeds/R/initPortableStreams.R’: assign("currentStream", n, envir = .GlobalEnv) assign("currentStates", curStates, envir = .GlobalEnv) assign("currentStream", 1L, envir = .GlobalEnv) assign("startStates", runSeeds, envir = .GlobalEnv) assign("currentStates", runSeeds, envir = .GlobalEnv) assign("currentStream", as.integer(currentStream), envir = .GlobalEnv) assign("startStates", runSeeds, envir = .GlobalEnv) assign("currentStates", runSeeds, envir = .GlobalEnv) Altering the user's environment requires a special arrangement with CRAN. I believe this is justified, I'll sketch the reasons now. But, mostly, I'm at your mercy and if there is any way to make this possible, I would be very grateful. To control & replace random number streams, it really is necessary to alter the workspace. That's where the random generator state is stored. It is acknowledged in Robert Gentleman' s Book, R Programming for Bionformatics "The decision to have these [random generator] functions manipulate a global variable, .Random.seed, is slightly unfortunate as it makes it somewhat more difficult to manage several different random number streams simultaneously” (Gentleman, 2009, p. 201). I have developed an understandable set of wrapper functions that handle this. Some of you may recall this project. I've asked about it here a couple of times. We allow separate streams of randoms for different purposes within a single R run. There is a framework to save 1000s of those sets in a file, so it can be used on a cluster or in a single workstation. This is handy because, when 1 run in 10,000 on the cluster exhibits some weird behavior, we can easily re-initiate that interactively and see what's going on. I have a vignette "pps" that explains. I dropped a copy of that here in case you don't want to get the package: http://pj.freefaculty.org/scraps/pps.pdf While working on that, I gained a considerably deeper understanding of random generators and seeds. That is what this vignette is about http://pj.freefaculty.org/scraps/PRNG-basics.pdf We've been running simulations on our cluster with the portableParallelSeeds framework for 2 years, we've never had any trouble. We are able to re-start runs, verify random number draws in separate streams. PJ -- Paul E. Johnson Professor, Political Science Assoc. Director 1541 Lilac Lane, Room 504 Center for Research Methods University of Kansas University of Kansas http://pj.freefaculty.org http://quant.ku.edu ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
