[R] generating multivariate autocorrelated time series

[Paul Gilbert]

If you can specify an ARMA or state-space model for the vector process, 
then you can do this with simulate in the dse bundle.

Paul Gilbert

Thomas Petzoldt wrote:

>Hello expeRts,
>
>for an application in hydrology I need to generate multivariate 
>(log)normally distributed time series with given auto- and 
>cross-correlations. While this is simple for the univariate case (e.g. 
>with conditional normal sampling) it seems to be not so trivial for 
>multivariate time series (according to papers available about this topic).
>
>An example:
>
>I have several (e.g. 3) time series (which are, of course, *correlated* 
>measurements in reality):
>
>z <- ts(matrix(rnorm(300), 100, 3), start=c(1961, 1), frequency=12)
>
>and I want to get the vector for the next time step(s):
>
>z[n+1, 1:3]
>
>respecting the autocorrelations from that matrix up to a given lag value:
>
>a <- acf(z, lag=2)
>
>My question: Does anybody know about a solution (function, package, 
>example etc...) available in R?
>
>Thanks a lot!
>
>Thomas P.
>
>---
>http://tu-dresden.de/Members/thomas.petzoldt
>
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