[R] help about random generation of a Normal distribution ofseveral variables

[Bill.Venables at csiro.au]

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: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Peng Jiang
Sent: Sunday, 6 July 2008 1:47 PM
To: Arnau Mir Torres
Cc: r-help at 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) <Ted.Harding at manchester.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 05-Jul-08                                       Time: 18:09:23
------------------------------ XFMail ------------------------------

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On 2008-7-6, at 上午12:13, 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 at 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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