similar to: Reading in a value of .Random.seed in .Rprofile

I am (for my sins) having to do some work using R under Windoze. I wanted to set up a .Rprofile to control my set-up. The docs on .Rprofile say that it can/should be placed in ``the user's home directory''. ``An Introduction to R'' observes lucidly that this concept needs to be clarified under Windoze. Following the suggestions in An Introduction to R, I tried putting a

I did several simulation sessions and the result turned out to be a surprise. After some investigation, I found that different R sessions of the program used the same seed. Simply, in R210, if I start R and type rnorm(1), I always get the same random number. This is contradictary to what is in the R document Initially, there is no seed; a new one is created from the current time when one

Hello! I would like to be able to read in list data objects in R/S created in R/S. (Ie R->S or S->R.) I have tried 'dput' and 'dump' in S, but neither of the created files could be read into R (with 'dget' nor 'source'). Is there any way that I can save a list object in S that can be read into R? Sincerely, Zachary Skrivanek, PhD Research Scientist

Dear all, I was doing an experiment to disprove some theory therefore performing lot of random simulation. Goal is to show the audience that although something has very rare chance to occur but it doesn't mean that event would be impossible. In this case after getting that rare event I need to show that same scenario for multiple times to explain other audience. Hence I need to somehow

Full_Name: Lara Jamieson Version: 1.1.1 OS: Linux Submission from: (NULL) (131.111.20.203) I've checked for other reports on this and can't find anything. It seems that the .Random.seed isn't updated properly after using rm(.Random.seed). Mu understanding from the help file indicates that a new 'random' seed will be generated. It appears that sometimes the old one is just

Hi, How to save an R object for example a matrix or vector and not all objects created in a session (which is usually performed by save.image or q("yes"))? Best, Carol [[alternative HTML version deleted]]

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

On Debian/Ubuntu, system wide environment variables and options are set in respectively /etc/R/Renviron.site and /etc/R/Rprofile.site. These files are automatically created when r-base is installed, and do not get overwritten during an upgrade. On Fedora, there is no /etc/R directory. What is the recommended place to define system wide environment variables and options on a Fedora system?

Dear R-Helpers, I'm fiddling with my .Rprofile in Windows XP & R 2.7.0 Beta. I prefer to manually save my workspace but automatically save my command history via the .Rprofile. That is working fine once I found that "utils::" was required before the loadhistory & savehistory functions. What I would like to do is add a separator line with a date between the histories of each

Is it intentional that the .Random.seed is saved in .RData? If people run multiple sessions from the same directory they will get the same intial seed setting, which seems a bit dangerous. I don't often save my session nor run two sessions in the same directory, so I have never run it this, but there was a question on r-help where it may have been an issue. Paul Gilbert

I'm trying to source a file automatically every time I start R. I tried adding the following .First function in a file Rprofile.site in my $R_HOME/etc/ directory (verified $R_HOME by Sys.getenv()) as well as in a file .Rprofile in my $HOME directory and .Rprofile in the working directory: .First <- function(){ source(file.path(Sys.getenv("HOME"), "R",

Hi all, After a short hiatus away from R I have found that it's changed a bit. I used to keep a definition of .First in .Rprofile that did a couple of things on startup (load a couple of libraries). Now, I've discovered that when I change the definition of .First in .Rprofile it doesn't change anything when I start up, because .First is held over in .Rdata from the last session.

Dear all I'm using Xubuntu Lucid and I keep getting the same random numbers whenever I start a new session of R. For example, I keep getting > sample(1:1000, 1) [1] 87 or > rnorm(1:10) [1] -1.3618103 0.4241701 1.0720076 0.2208145 -0.5375314 -0.4846588 [7] 0.7576768 0.6527407 -0.6868786 0.8718527 I expected that some set.seed() instruction woudl be present in a config file in

If the "Matrix" package is attached, 'example(dget)' fails: > library(Matrix) > example(dget) dget> fil <- tempfile() dget> ## Write an ASCII version of function mean to our temp file dget> dput(mean, fil) dget> ## And read it back into 'bar' dget> bar <- dget(fil) Error in initialize(value, ...) : '...' used in

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

Dear R-Developers and -Community, after compiling and installing R 1.2.2., I started 'demo(graphics)' for a test, and got: 'Error in rnorm(0): .Random.seed(0) is not a Normal type' Obviously .Random.seed was not initialized appropriately. Following the the documentation for '.Random.seed' [see below 'Examples'], this can be fixed rm(.Random.seed);

It could be that the following may be due to something wrong that I managed to do (I cannot think what...) but I submit this report in case it is something that you want to know about (I have solved the problem by removing .Rprofile as I describe below). 1. After compiling/installing R 0.90 (an uneventful process), it worked perfectly the first time, and it read .RData written by the previous

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

I use the ugly hack shown below as my .Rprofile (mainly because I couldn't find any other way to spawn a new mozilla window on starting R or calling help.start(), but then send all the help html documents to that new window). With a recent change from a cvs checkout to the released 1.9.0 I find that the new hs() appears if there is nothing of that name in .RData, but if there is the old hs()

Hi, this is related to a question just raised on Bioconductor where one function sets the random seed internally but never resets it, which results in enforced down streams random samples being deterministic. What is the best way to reset the random seed when you use set.seed() within a function? Is it still to re-assign '.Random.seed' in the global environment as following example