similar to: R-alpha: random number generator

Dear all, Recently I am generating large random samples (10M) and any duplicated numbers are not desired. We tried several RNGs in R and found Wichmann-Hill did not produce duplications. The duplication problem is the interesting birthday problem. If there are M possible numbers, randomly draw N numbers from them, the average number of dupilcations D = N(N-1)/2/M. For Knuth-TAOCP and

Not sure what should happen theoretically for the code in vseq.c, but I see the same pattern with the R generators I tried (default, Super-Duper, and L'Ecuyer) and with with bash $RANDOM using N <- 10000 X1 <- replicate(N, as.integer(system("bash -c 'echo $RANDOM'", intern = TRUE))) X2 <- replicate(N, as.integer(system("bash -c 'echo $RANDOM'",

This question may not be specific to R, but I'm using R so here goes: Since R is slow (as is Splus) I want to split a simulation and run it on 2 or 3 systems at once. The simulations involve generating a large number of random values. How can I set .Random.seed so that the succession of random values don't overlap across systems. I see that when I invoke R and give command runif(1) a

R 0.64 on windows NT 4.0 Sometimes I got an error message by doing this > .Random.seed <- c(1, 1:2) > .Random.seed [1] 1 1 2 > runif(5) Warning: Wrong length .Random.seed; forgot initial RNGkind? set to Wichmann-Hill[1] 0.02253721 0.84832584 ........ Sometimes I do not get error message: > .Random.seed <- c(1, 1:2) > .Random.seed [1] 1 1 2 > runif(1) [1] 0.5641106 >

--Multipart_Mon_Nov_24_14:51:09_1997-1 Content-Type: text/plain; charset=US-ASCII >>>>> "PaulG" == Paul Gilbert <pgilbert@bank-banque-canada.ca> writes: MM> The code is basically in V&R 1 and 2; V&R2 on p.167. I have it as a MM> C function that I used to dyn.load into S-plus in order MM> to prove that S-plus was using it.

As some of you know, we have been thinking of allowing the possibility of a CHOICE of the kind of random number generator (=: RNG) to use in R. The current R-release snapshot even has some code in it; however, this will be changed quite a bit. Here is a kind of informal RFC (request for comments / request for criticism / ..): 1a. With the new scheme, we still want that save(..) &

Hi, I have a few questions about the RNG in R; apologies if these are dumb questions: 1. It is my understanding that, among the three types of random number generators available in R now, the best one is the Marsaglia Multicarry. Is this correct? 2. How does the best RNG in R compare (in terms of quality) to the RNG in SPlus? (based on Marsaglia's Super Duper)? Does the Super-Duper in

I''m doing some simulations for which i need to use both S-plus and R. I generate in S+ some random normal distributions to define one dataset by iteration. I need to use the same dataset generated in S-plus in R. I was first thinking to generate in R the same dataset by using the same random number generator with a fixed seed. But It seems that S-plus and R don''t use the same

Dear All, The editor of a journal to which I had submitted a publication asked whether R has a "tested random number generator." My paper included Monte Carlo simulations generating random normal and random chi-square values. help(rnorm) lists Wichura, M. J. (1988) Algorithm AS 241: The Percentage Points of the Normal Distribution. Applied Statistics, 37, 477-484. as a

On 9/21/18 6:38 PM, Tierney, Luke wrote: > Not sure what should happen theoretically for the code in vseq.c, but > I see the same pattern with the R generators I tried (default, > Super-Duper, and L'Ecuyer) and with with bash $RANDOM using > > N <- 10000 > X1 <- replicate(N, as.integer(system("bash -c 'echo $RANDOM'", intern = TRUE))) > X2 <-

Hi this is my first post. I am trying to run a simulation for a computer playing Von Neumann poker and adjusting it's expectation of an opponent's behavior according to how the opponent plays. This program involves random generation of "hands" and shifting of parameters. However, when I run the code, no errors come up, but the program doesn't do anything. Could someone

Hi, I'm looking for a super-duper fast mean/sum binning implementation available in R, and before implementing z = binnedMeans(x y) in native code myself, does any one know of an existing function/package for this? I'm sure it already exists. So, given data (x,y) and B bins bx[1] < bx[2] < ... < bx[B] < bx[B+1], I'd like to calculate the binned means (or sums)

Dear Sir/Madam, I am a beginner in R. Here is my questions. 1. Can you give me one test for randomness (a name and descriptive paragraph is sufficient). 2. I have learned a uniform random number generator [e.g. not the algorithms: i)Wichmann-Hill, ii) Marsaglia-Multicarry, iii) Super-Duper (Marsaglia), iv) Mersenne-Twister, v) TAOCP-1997 (Knuth), or vi) TAOCP-2002 (Knuth)] . Is there any other

I would like to move an existing W2K3 install onto my new super duper xen box -- Installing linux based machine is no issue, it''s the windows ones that keep getting me. I have Acronis which we usually use for bare metal restores, and it seems that bare metal restores don''t want to work too well with XEN, any assistance/help/ideas ?

Hello, On Thursday, September 20, 2018 11:15:04 AM EDT Duncan Murdoch wrote: > On 20/09/2018 6:59 AM, Ralf Stubner wrote: > > On 9/20/18 1:43 AM, Carl Boettiger wrote: > >> For a well-tested C algorithm, based on my reading of Lemire, the > >> unbiased "algorithm 3" in https://arxiv.org/abs/1805.10941 is part > >> already of the C standard library in

Here is my situation: 1. We use Active directory (LDAP) to store all user info which is retrieved from linux 2. A home directory is not created until the first time the user logs into the linux system I am using the ssh_authorized_key type to push out my ssh keys to every system. However, because I haven''t logged into every system at least once. Puppet errors out due to a missing

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. ---559023410-851401618-1218751024=:15885 Content-Type: TEXT/PLAIN; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE I didn't describe the problem clearly. It's about the number of distinct=20 values. So just

I wonder - do we have some helper/processor/gem to automatically convert all URLs in a passed string to their canonical equivalent - i.e. with the protocol, host and such prepended based on the Rails environment. Super-duper infty for RSS feeds (I hate their requirement for canonical URLs everywhere). -- Julian ''Julik'' Tarkhanov please send all personal mail to me at

Dear list, For the implementation of a particular optimization algorithm it is very important the random number generator. I would like to know if somebody could tell me what is the random number generator used by default in the 'runif' function. >From the help page of 'runif' and '.Random.seed' I guess that the default algorithm is 'Mersenne-Twister', but I

Hi, As you probably know, there is a problem with the interface for adding uniform random number generators in R (see by article in R News 5/2, November 2005). There exists a mechanism called "user-supplied" that allows users of R to run their own generator in R. However, there is no such mechanism for package writers. Those who want to add their own generators abuse