similar to: .Random.seed error

hello all, I use the R standalone math library in my own C program, and the default R random number generator can be seeded with set_seed(const unsigned int, const unsigned int). How could I seed the RNG with an instance of .Random.seed ? I would need this or a similar workaround for debugging purposes. More precisely, I use the default R random number generator to sample from various

I'm running R-2.0.0 (yesterday's snapshot)in its own directory, and everything works great, except: > .Random.seed Error: Object ".Random.seed" not found Does 2.0.0 not use .Random.seed for saving, etc, like it says in the help page? Thanks for any help. -Frank

Dear expeRts, I struggle with the following problem using snow clusters for parallel computing: I would like to specify l'Ecuyer's random number generator. Base R creates a .Random.seed of length 7, the first value indicating the kind fo random number generator. I would thus like to use the components 2 to 7 as the seed for l'Ecuyer's random number generator. By doing so, I

Hi All, I have k identical parallel pieces of code running, each using n.rand random numbers.? I would like to use the same RNG (for now), and set the seeds so that I can guarantee that there are no overlaps in the random numbers sampled by the k pieces of code.? Another side goal is to have reproducibility of my results.? In?the past I have used C with SPRNG for this task, but I'm hoping

Hi, The problem arises when I lazyLoad() the .Random.seed from a previously saved database. To simplify the process of reproducing the problem, see the example below: ## this assignment may not really make sense, but illustrates the problem delayedAssign('.Random.seed', 1L) typeof(.Random.seed) # [1] "integer" rnorm(1) # Error in rnorm(1) : # .Random.seed is not an integer

Hi, The problem arises when I lazyLoad() the .Random.seed from a previously saved database. To simplify the process of reproducing the problem, see the example below: ## this assignment may not really make sense, but illustrates the problem delayedAssign('.Random.seed', 1L) typeof(.Random.seed) # [1] "integer" rnorm(1) # Error in rnorm(1) : # .Random.seed is not an integer

On Sun, Mar 4, 2018 at 3:23 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 04/03/2018 5:54 PM, Henrik Bengtsson wrote: >> >> The following helps identify when .GlobalEnv$.Random.seed has changed: >> >> rng_tracker <- local({ >> last <- .GlobalEnv$.Random.seed >> function(...) { >> curr <- .GlobalEnv$.Random.seed

Thank you, everybody, who replied! I appreciate your valuable advise! I will move the location of the set.seed() command to after all packages have been installed and loaded. Best regards, Gary Sent from my iPad > On Mar 4, 2018, at 12:18 PM, Paul Gilbert <pgilbert902 at gmail.com> wrote: > > On Mon, Feb 26, 2018 at 3:25 PM, Gary Black <gwblack001 at sbcglobal.net> >

Dear R-help, Suppose I write a script that looks something like this: #### script.R set.seed(something) x <- rnorm(100) y <- runif(500) # bunch of other stuff save.image() ### end of script.R Now, I give you a copy of my script.R (with the set.seed statement removed, of course) together with the .RData file that was generated by the save.image() command. Question: 1) can you tell

sorry but I don't understand exactly what you mean. When I create a new user I'm logged in as root. How can I create a new user with an trust account?? -----Urspr?ngliche Nachricht----- Von: rod@newtonhall.co.uk [mailto:rod@newtonhall.co.uk] Gesendet: Mittwoch, 9. Oktober 2002 13:45 An: Gianluca Urbano Betreff: Re: [Samba] New User in Samba 2.2.4 i'm new 2, but i think u need a

Buenas, tengo la siguiente inquietud. Tengo un data frame con los microdatos de la ECH de mi pais. He realizado un cuadro sin problemas en excel pero me gustaria una rutina de R para poder generar la tabla. El data.frame se llama ECH2009. Cuenta con las siguientes variables para este caso: idhogar region estrato integranteshogar expansor ingpercapsvl Computador TvAbonado Internet 1 capital 1 2

On 04/03/2018 5:54 PM, Henrik Bengtsson wrote: > The following helps identify when .GlobalEnv$.Random.seed has changed: > > rng_tracker <- local({ > last <- .GlobalEnv$.Random.seed > function(...) { > curr <- .GlobalEnv$.Random.seed > if (!identical(curr, last)) { > warning(".Random.seed changed") > last <<- curr

Thanks much Ted. I actually had just tried what you suggest here before you posted, and resolved the problem. Thanks also for the other tips. I wrote x = as.vector(c(1:12)) because I thought that the mode of x might be the problem, the error message pointing to .Random.seed notwithstanding. On a related note, I did a brief test a couple weeks back where I ran a million random samples of 3 from

Hi I am experiencing a problem with the random number generator. When I call any function that involve RNG such as "runif" or "sample" I get this error: .Random.seed is not an integer vector but of type 'double' I can't coerce the random seed and it's recommended not to alter it anyway. Can anybody help me? Thanks and kind regards, Piero Visconti, PhD

The following helps identify when .GlobalEnv$.Random.seed has changed: rng_tracker <- local({ last <- .GlobalEnv$.Random.seed function(...) { curr <- .GlobalEnv$.Random.seed if (!identical(curr, last)) { warning(".Random.seed changed") last <<- curr } TRUE } }) addTaskCallback(rng_tracker, name = "RNG tracker") EXAMPLE: >

On 04/11/2017 10:20 PM, Daniel Nordlund wrote: > Tirthankar, > > "random number generators" do not produce random numbers. Any given > generator produces a fixed sequence of numbers that appear to meet > various tests of randomness. By picking a seed you enter that sequence > in a particular place and subsequent numbers in the sequence appear to > be unrelated.

In case you don't get an answer from someone more knowledgeable: 1. I don't know. 2. But it is possible that other packages that are loaded after set.seed() fool with the RNG. 3. So I would call set.seed just before you invoke each random number generation to be safe. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking

On Mon, Feb 26, 2018 at 3:25 PM, Gary Black <gwblack001 at sbcglobal.net> wrote: (Sorry to be a bit slow responding.) You have not supplied a complete example, which would be good in this case because what you are suggesting could be a serious bug in R or a package. Serious journals require reproducibility these days. For example, JSS is very clear on this point. To your question >

Hello! I am performing coupling of chains in MCMC and I need the same value of seed for two chains. I will show demo of what I want: R code, which might show my example is: niter <- 3 nchain <- 2 tmpSeed <- 123 for (i in 1:niter) { # iterations for (j in 1:nchain) { # chains set.seed(tmpSeed) a <- runif(1) cat("iter:", i, "chain:", j,

Dear r-helpers, Could you please help me solve the following problem: When I run require(AlgDesign) trt <- LETTERS[1:5] blk <- 10 trtblk <- 3 BIB <- optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) In response to the last command, R complains: Error in optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) : object ".Random.seed" not found The