
Hi,

I actually largely solved the problem, i am using this code:

var1 <- rnorm(5000,0,5)
var2 <- 0.90*var1+0.10*rnorm(5000,0,10)
plot(var1,var2)

Its somewhat simplistic to say the least but it works more or less,  i will
definantly look into your suggestion though!

Thanks
Thor
Denmark


On Sun, Sep 12, 2010 at 12:23 AM, Dennis Murphy [via R] <
ml-node+2535974-1500011135-160400@n4.nabble.com<ml-node%2B2535974-1500011135-160400@n4.nabble.com>
> wrote:

> Hi:
>
> Do you mean multinomial or multivariate normal? If the latter, then in
> addition to the previous response, there is package mvtnorm and a function
> mvrnorm() in the MASS package to generate correlated multivariate normal
> samples.
>
> HTH,
> Dennis
>
> On Sat, Sep 11, 2010 at 12:52 PM, thedreamshaper
> <[hidden email] <http://user/SendEmail.jtp?type=node&node=2535974&i=0>>wrote:
>
>
> >
> > I have had plenty of succes generating one dimensional variables and
> > plotting
> > them, but what do i do for more (specifically 2) dimensional multinomial
> > variables?
> >
> > I figure i have to create a vector consisting of two 1 dim normallly
> > distributed variables, that way i can also control the correlation.
> >
> > But how do i do this :) ?
> >
> > Many thanks
> > --
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