# [R-SIG-Finance] time series question

spencerg spencer.graves at prodsyse.com
Sat May 23 20:57:16 CEST 2009

```      Have you tried the corARMA capabilities in the lme function, nlme
(https://stat.ethz.ch/pipermail/r-sig-finance/2009q2/004152.html)?  I'm
not sure, but I believe you can either get one set of estimates or one
for each series, estimating between-series variances, etc.  If so, you
can also test hypotheses such as whether the ARMA models for the
different series are different.  Moreover, the different series can be
of different lengths.

Hope this helps.
Spencer Graves

Ajay Shah wrote:
> On Fri, May 22, 2009 at 08:13:25PM -0500, markleeds at verizon.net wrote:
>
>> Hi everyone: Normally, if one has a single realization of a time series and one wants to estimate
>> say an ARMA(p,q) , where p and q are known ( for simplicity )  then one estimates it and that's that.
>>
>> But, suppose that one has more than one realization  of the time series ( assuming each series is the same length) and yet still wants to estimate the "best" arma(p,q) , over all the realizations,  again where p and q are known.
>>
>
> Could we perhaps think of this as follows.
>
> We are holding two realisations from the same process:
>    x1, x2, ... xN
>    y1, y2, ... yN
>
> and let's suppose these two realisations are completely
> independent. Think of two parallel experiments running with the
> identical data generating process but a different set of random
> shocks.
>
> Then you could construct the overall log likelihood of what you have
> observed as logl(theta; x) + logl(theta; y) and maximise that.
>
> Is there an existing R function off the shelf which yields the ARMA
> log likelihood? If so then it should be easy to put together an
> overall logl() function for this problem which can be then given to
> optim() to do estimation.
>
>

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