Re: Out of sample prediction

[DAVE REILLY]

va

   In general you should not be using regression as your problem
involves time series
http://stats.mth.uea.ac.uk/wiki/statwiki/TimeSeries.html might be of
some help in this regard.

   In particular it appears to me that that your problem is as follows


 Y   X

y1,1   0.
y2,1   0.
y3,1   0.


   yn,10.   where n is the
last observation in period 1

   y1,2   .2
   y2,2   .4
   y3,2   .45
   y4,2   .5
   y5,2   .6
   y6,2   .6

   .

   ym,2  .6




  where .2,.4,.45,.5,6,.,6..6

  reflects some assumption about growth in the second period ...leveling
off



 suggested steps

 1. Build an ARIMA model for y1,1 through yn,1
 2. Create a Transfer Function  of  Y(T)  = W(B)*X(T) + ARIMA
 3. Forecast from last observation in the first period.

This is easily done with AUTOBOX as it allows the user to pre-specify
not only the form of the model but the parameters ( in this case it is a
mixed bag empirical coefficients and form for the ARIMA component
and a user specification for the Causal component.


regards

Dave Reilly

http://www.autobox.com


P.S. If you would like we would be more than happy to demonstrate this
capability. Please call me at 215-675-0652 to discuss the details.



Victor Aina wrote:

> Hi everyone:
>
> I've got 2 non-overlapping periods. Data is
> available for period one (the first period).
> The intention is to predict observations that
> will be coming in period 2.
>
> Now, suppose an extra information is available for
> period 2. In particular, suppose it is known that
> the values of observations in the 1st half of
> period two will increase, and thereafter level off.
>
> My question is what options are available for
> capturing (in a regression model) such problem?
> And what are the caveats and/or pitfalls?
>
> Thanks for your insight.
>
> --
>
> +--+
> | victor aina  |  e-mail: [EMAIL PROTECTED] | fax:(604) 291-5944 |



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Re: Exploratory data analysis

[DAVE REILLY]

 We have some material on the subject you raise.

 http://www.autobox.com/outlier.html

as it deals with exploratory data analysis ( hypothesis generation )

also

please see

http://www.autobox.com/whatis.html

If they are useful to you, please let me and the group know.

regards

Dave Reilly



Ken wrote:

> Try
>
> http://www.itl.nist.gov/div898/handbook/eda/eda.htm
>
> and here's one that will give you a headache
>
> http://seamonkey.ed.asu.edu/~behrens/asu/reports/Peirce/Logic_of_EDA.html
>
> Jostein Vada wrote:
>
> > Hi,
> > I am a norwegian PhD student within the field of process control,
> > and in 7 days I am going to defend my thesis. One part of the "exam" is
> > to give a lecture on subject which is unknown to me. Six days ago I
> > received the title:
> >
> > "Exploratory Process Data Analysis"
> >
> > Focus is on methods and theory for the data-processing stage of model
> > developement. Issues should include nonlinear filtering techniques,
> > robust statistics, redundant techniques for data analysis, data
> > reconciliation, and graphical examination of data. In other words, the
> > process from raw data until model identification.
> >
> > As far as I know, there is a huge amont of litterature on all these
> > issues. Does anyone know of  books, papers or webpages which give a
> > survey over this field?
> >
> > I'll be appreciated for any information.
> >
> > Jostein Vada



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