search for: seed

Hello again, I was testing today's SNAP (openssh-SNAP-20000830.tar.gz) in my Solaris 2.6-8 environment, when I found some problems with the ssh2 support. While connecting, it seeds the RNG something like 32 times! And then once connected, it seeds again 2 or 3 times with *every* keystroke! This makes for some slow going. This happens on all of the Solaris boxes I tried. Binary was compiled on 2.6 against OpenSSL 0.9.5a. Output follows: 6:19pm.orangecrush: ~# ssh -2...

Could someone please suggest a method to store the current random seed. I'm having trouble understanding how to correctly use set.seed and .Random.seed. Specifically, I have the following code that crashes: set.seed(seed) for(i in 1:10){ print( runif(1)) } To get around this I need to split the number of iterations into chunks: set.seed(seed) for(i...

I have noticed that when I iterate permutations of short vectors with the same seed, the cycle lengths are much shorter than I would expect by chance. For example: X <- 1:10 Xorig <- X start <- 112358 N <- 10 for (i in 1:N) { seed <- start + i for (j in 1:1000) { # Maximum cycle length to consider set.seed(seed) # Re-seed RNG to same initial state X...

...a permutation is decomposed into cycles and how the order relates to a partition of n (n=10 in your case). Enjoy! Eric On Fri, Dec 8, 2017 at 6:39 AM, Boris Steipe <boris.steipe at utoronto.ca> wrote: > I have noticed that when I iterate permutations of short vectors with the > same seed, the cycle lengths are much shorter than I would expect by > chance. For example: > > X <- 1:10 > Xorig <- X > start <- 112358 > N <- 10 > > for (i in 1:N) { > seed <- start + i > for (j in 1:1000) { # Maximum cycle length to consider > set.se...

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...

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 > }...

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 >> if (!identical(curr, last)) { >> warning(".Random.seed changed") >>...

...te 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 > My question simply is: should the location of the set.seed command matter, > provided that it is applied before any commands which involve randomness > (such as partitioning)? the answer is no, it should not matter. But the proviso is important. You can determine where things are messing up using something like set.seed(654321) zk <- RNG...

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 rnor...

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 rnor...

I'm having trouble loading ggplot2 on my mac (Snow Leopard) using R version 2.12.1, as shown below. I can't find a posting relevant to this problem, so any help would be very much appreciated. Thanks, peter l > install.packages('ggplot2', dep = TRUE) trying URL

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> > wrote: >...

...ely. STORE command also seemed to be buggy, giving lots of "STORE failed" errors, even with just one connection. Zimbra uses 500MB of memory just to start up, so it's not exactly for hosting small installations. Login+Logout ------------ Dovecot: ./imaptest - select=0 secs=10 seed=0 clients=1 Logi Logo 100% 100% 3439 6878 ./imaptest - select=0 secs=10 seed=0 clients=10 Logi Logo 100% 100% 4415 8830 Zimbra: ./imaptest - select=0 secs=10 seed=0 clients=1 Logi Logo 100% 100% 18032 36064 ./imaptest - select=0 secs=10 seed=0 clients=10 Logi Logo 100% 100%...

...the size of the fonts (especially the axes and axes labels) to be bigger! Thanks so much! Here is my code: # Poster figure 1 stationmean=c(19.4833,10.8000) fieldmean=c(14.6852, 15.5981) plot(c(0,1),fieldmean,xaxt='n',type="b",pch=20,col="green3", main="Foxtail Seeds Remaining vs.Field Type", ylab="Mean Number Foxtail Seeds Remaining", xlab="Field Type",ylim=c(10,20),xlim=c(-.25,1.25)) axis(1,at=c(0,1),labels=c("Cover Crop","Wheat Stubble")) # Poster figure 2 stationmean=c(19.4833,10.8000) fieldmean=c(14.6852, 15...

...m: 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 documentation of optBlock() in AlgDesign doesn't say that I needed to set .Random.seed. I thought it was initiated automatically at the beginning of a session. What am I missing? > sessionInfo() R version 2.4.1 (2006-12-18) i386-apple-darwin8.8.1 locale: C attach...

Dear expeRts, ./src/library/base/man/Random.Rd says that L'Ecuyer requires a seed of length 6. ./src/library/parallel/man/RngStream.Rd also mentions this, but only in the text part; In the "Arguments"-part, it says that "seed" has to be of length 7 Also: ,---- | > RNGkind("L'Ecuyer-CMRG") | > length(.Random.seed) | [...

Hello, does LLVM already have a Random Number Generator built into it's library somewhere? I know code generation is suppose to be deterministic, but when producing a random number can be deterministic if the random number generator is also deterministic. - Thanks - Jeff Kunkel

Hi, In the R console, I have the following: > runif(10) Error in runif(10) : '.Random.seed' is not an integer vector but of type 'list' > Can someone advise me of the solution of the problem? Mei-Yuan Chen Department of Finance NCHU, aiwan

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] 0.564...

...I dont know if anyone else has noticed the same thing, but with 2 subsequent runs of the same syntax, I am getting exactly the same results. I was expecting that results differ slighlty, say in the 4th or 5th decimal place. Is this a specialty with R2WinBUGS? Does it have something to do with the seed value? Isnt the seed value reset everytime I restart winbugs? Thanks Toby