Thanks!

On Sun, Jun 17, 2012 at 1:18 AM, Miguel Manese <jjonphl@gmail.com> wrote:

> Hi Al, Michael,
>
> On Sat, Jun 16, 2012 at 11:01 AM, R. Michael Weylandt
> <michael.weylandt@gmail.com> wrote:
> > On Fri, Jun 15, 2012 at 6:56 AM, Al Ehan <aehan3616@gmail.com> wrote:
> >> Hi,
> >>
> >> I would like to make a replication of 10 of a linear, first order
> >> Autoregressive function, with respect to the replication of its
> innovation,
> >> e. for example:
> >>
> >> #where e is a random variables of innovation (from GEV distribution-that
> >> explains the rgev)
> >> #by using the arima.sim model from TSA package, I try to produce Y
> >> replicates, with respect to every replicates of e,
> >> #means for e[,1], I want to have say Y[,1].
> >>
> >> The code:
> >>
> >> e=replicate(10,rgev(20,xi=0.2,mu= 931.1512,sigma= 168.2702 ))
> >> Y=replicate(10,ts(arima.sim(list(ar=0.775),n=20,innov=e,start.innov=e)))
> >>
> >> what I get is the same random variables for every replicates of Y.
> >
> > Well, what would you expect? You're passing the same values of e each
> > time. What you probably want to do is to put the rgev call as the
> > innov argument to arima.sim(). Take a look at the second example of
> > ?arima.sim to see how its done (change the rt to rgev and you're good
> > to go.
> >
>
> More specifically, you'd do something like
>
> Y <- replicate(10, ts(arima.sim(list(ar=0.775), n=20, rand.gen=rgev,
> xi=0.2, mu=931.1512, sigma=168.2702)))
>
>
> - Jon
>

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