What's the problem with loading the MASS library??? The MASS library is one of the recommended packages, so should be universally available.
Pinching code like this and freezing it inside your personal scripts means that if ever we find bug fixes or improvements you miss out on them. Bill Venables CSIRO Laboratories AUSTRALIA http://www.cmis.csiro.au/bill.venables/ -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Peng Jiang Sent: Sunday, 6 July 2008 1:47 PM To: Arnau Mir Torres Cc: r-help@r-project.org Subject: Re: [R] help about random generation of a Normal distribution ofseveral variables Hi , Arnau Did you ever check your mailbox? your question was answered last night Beijing time. :) Just read the following . ------------------------- There is no need to load the MASS library, since the code for mvrnorm therein is compact and self-contained: mvrnorm <- function (n=1, mu, Sigma, tol=1e-06, empirical=FALSE) { p <- length(mu) if(!all(dim(Sigma) == c(p, p))) stop("incompatible arguments") eS <- eigen(Sigma, symmetric = TRUE, EISPACK = TRUE) ev <- eS$values if(!all(ev >= -tol * abs(ev[1]))) stop("'Sigma' is not positive definite") X <- matrix(rnorm(p * n), n) if(empirical) { X <- scale(X, TRUE, FALSE) X <- X %*% svd(X, nu = 0)$v X <- scale(X, FALSE, TRUE) } X <- drop(mu) + eS$vectors %*% diag(sqrt(pmax(ev, 0)), p) %*% t(X) nm <- names(mu) if(is.null(nm) && !is.null(dn <- dimnames(Sigma))) nm <- dn[[1]] dimnames(X) <- list(nm, NULL) if(n == 1) drop(X) else t(X) } Define that function as above, then proceed along the lines suggested by Gavin Simpson below. Ted. On 05-Jul-08 16:43:46, Gavin Simpson wrote: > On Sat, 2008-07-05 at 18:21 +0200, Arnau Mir wrote: >> Hello. >> >> Somebody knows how can I generate a set of n random vectors of a >> normal distribution of several variables? >> For example, I want to generate n=100 random vectors of two >> dimensions for a normal with mean c(0,1) and variance matrix: >> matrix(c(2,1,1,3),2,2). > > One is mvrnorm() in the MASS package, part of the VR bundle that comes > with R. > >> require(MASS) >> mu <- c(0,1) >> Sigma <- matrix(c(2,1,1,3),2,2) >> res <- mvrnorm(100, mu = mu, Sigma = Sigma) >> head(res) > [,1] [,2] > [1,] 2.7582876 1.04208798 > [2,] 0.6364184 -0.08043244 > [3,] -1.8897731 0.04051395 > [4,] 2.6699881 0.83163661 > [5,] -1.1942385 -1.17503716 > [6,] -0.4303459 -0.80880649 > > HTH > > G -------------------------------------------------------------------- E-Mail: (Ted Harding) <[EMAIL PROTECTED]> Fax-to-email: +44 (0)870 094 0861 Date: 05-Jul-08 Time: 18:09:23 ------------------------------ XFMail ------------------------------ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. On 2008-7-6, at 上åˆ12:13, Arnau Mir Torres wrote: > Hello. > > Somebody knows how can I generate a set of n random vectors of a > normal distribution of several variables? > For example, I want to generate n=100 random vectors of two > dimensions for a normal with mean c(0,1) and variance matrix: > matrix(c(2,1,1,3),2,2). > > Thanks in advance, > > Arnau. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
