Sums of correlated increments have the same correlation as the original
variables...
library(mvtnorm)
X<- matrix(0,nrow=1000,ncol=2)
for(i in 1:1000){
Y <- rmvnorm(1000,mean=mu,sigma=S)
X[i,] <- apply(Y,2,sum)
}
cor(Y)
[,1] [,2]
[1,] 1.0000000 0.4909281
[2,] 0.4909281 1.0000000
So, unless you meant that you want the _sample_ correlation to be
pre-specified, you are all set.
albyn
On Sun, May 09, 2010 at 09:20:25PM -0400, Sergio Andrés Estay Cabrera wrote:
> Hi everybody,
>
>
> I am trying to generate two random walks with an specific correlation, for
> example, two random walks of 200 time steps with a correlation 0.7.
>
> I built the random walks with:
>
> x<-cumsum(rnorm(200, mean=0,sd=1))
> y<-cumsum(rnorm(200, mean=0,sd=1))
>
> but I don't know how to fix the correlation between them.
>
> With white noise is easy to fix the correlation using the function rmvnorm
> in the package mvtnorm
>
> I surfed in the web in the searchable mail archives in the R web site but
> no references appears.
>
> If you have some advices to solve this problems I would be very thankful.
>
> Thanks in advance.
>
> Sergio A. Estay
> *CASEB *
> Departamento de Ecología
> Universidad Catolica de Chile
>
> --
> “La disciplina no tiene ningún mérito en circunstancias ideales. ” – Habor
> Mallow
>
> ______________________________________________
> R-help@r-project.org mailing list
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> 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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