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
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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.
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