Re: Time series prediction

[Juan Pablo Carbajal]

On Fri, Dec 30, 2011 at 11:48 PM, miro99_ale <address@hidden> wrote:
> Hi everybody,
> I need your help! :-)
> I have a series of data, registered from a sensor regarding the power
> consuming of a server in a time series... Something like this:
>
> timestamp   power
> 5   288,6
> 16   289,1
> 26   289,4
> 80   286,3
> 134   286,3
> 190   288,2
> 244   ...
>
> What I intended to do is to configure a time series predictor with octave in
> order to obtain the best ever possibile prediction on the next value (I have
> a set of constraints on the data to respect, e.g. data < 300 W, so I need
> the most accurate prediction as possible).
> The increasing gap between the timestamp is not a problem: I can assume this
> is a discrete time series and timestamp could also be called "1, 2, 3, 4,
> etc"...
> So, how I could solve this mess?
> I already read something about time series prediction, here in the general
> forum, that suggest the use of TISEAN or something related to the System
> Identification Toolbox... Anyway, what I think I really need, before a magic
> code which solve my problem, is a way to act:
> - I need to identify an ARMA model on my data? How I can do it with octave?
> - I need to calculate the W(z)? How I can do it with octave?
> - Which is the minimum number of data whit which I could have an optimum
> prediction?
> - How I can calculate the probability that the prediction match with the
> next real value? How I can do it with octave?
>
> Waiting your reply
> Best Regards
>
> Alessandro
>
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Sorry for the quick answer...I am traveling, not much inet access.

Check out the control package, arma, armax models were there last time
I saw. Otherwise just check wikipedia for armax and you will find all
the instructions to  implement your own.


-- 
M. Sc. Juan Pablo Carbajal
-----
PhD Student
University of Zürich
http://ailab.ifi.uzh.ch/carbajal/