coming from data mining and machine learning i have the following question which may or may not sound stupid for you, but as i have no clue and there are no stupid questions (just stupid answers) i take my chance posting the question to this list:

I already figured out how to fit an ARIMA process to my data (ok, how to actually find GOOD AR/MA/difference orders would be another question). And i can save the resulting model as Icon to my session. Does that mean i can also apply my model to any other data (of the same type of course)? Let's say i fit my model against a timeseries range A. How can i find out how my model fits to another timeseries range B? Maybe this isn't possible at all and i am misunderstanding the whole concept of ARIMA models and -forecasting. I am primary working with the data mining tool "RapidMiner", which allows you to easily apply any learned model to new and unseen data (classification mainly, but regression as well) and i wonder if it is the same with an estimated ARIMA model.

By the way, i appreciate that case markers can now be up to 15 chars in length, but what are they actually used for? Of course i'd like to have them show up on my plots, which i currently do by manually tweaking the gnuplot commands, but i think this functionality is still missing in gretl, am i correct? So what's left? Is there any practical use-case for case markers in timeseries analysis?

> In a gretl script, there's no limit to the extent to which you can > use an existing model as the basis for a new one.  Just copy, > paste and edit. Actually, I thought that what Oliver had in mind when he spoke of a model was the estimated coefficients as well, not "just" the general specification. Then it wouldn't be so easy I guess, because a saved model in gretl terms is tied to the used data sample as well, right? But maybe I didn't understand him correctly...

Oliver Heering schrieb: > The thing in gretl is, if i want to see how my estimated (on series A) > model performs on series B, i don't know how to actually do this > without fitting the model again, since i believe what Sven wrote: "a > saved model in gretl terms is tied to the used data sample as well". > > Please correct me, if i'm wrong. :-) Well in a script you can of course retrieve and store the coefficient vector of your model ($coeff) for further use. That wouldn't be so difficult, but it's not a one-liner.

On Tue, 1 Sep 2009, Allin Cottrell wrote: > On Tue, 1 Sep 2009, Sven Schreiber wrote: > > > Oliver Heering schrieb: > > > > > The thing in gretl is, if i want to see how my estimated (on series A) > > > model performs on series B, i don't know how to actually do this > > > without fitting the model again, since i believe what Sven wrote: "a > > > saved model in gretl terms is tied to the used data sample as well". > > > > > > Please correct me, if i'm wrong. :-) > > > > Well in a script you can of course retrieve and store the coefficient > > vector of your model ($coeff) for further use. That wouldn't be so > > difficult, but it's not a one-liner. > > In script mode you can do this sort of thing: > > open data9-7 > series y = QNC > arma 1 1 ; y > fcast yd1 --dynamic > y = INCOME > fcast yd2 --dynamic > > After replacement of the series "y", the series yd2 will contain > dynamic forecasts for INCOME using the model estimated for QNC. > This won't work for static forecasts because in that case gretl > just outputs the fitted values that are saved with the original > model.  But dynamic forecasts are generated de novo so you can > "trick" gretl into using a different series. I should perhaps point out that the task in hand here is easily performed for linear models, as shown below. <script> list X = 0 INCOME PRIME QNC(-1) ols QNC X matrix b = $coeff # switch QNC -> STOCK X = 0 INCOME PRIME STOCK(-1) # use padding zeros to cover the missing lag matrix Xm = zeros(1,4) | { X } Xm series yh = Xm*b print yh </script> This script generates, in yh, a fitted series for the STOCK variable using the model estimated on QNC. With ARIMA models it's trickier, and in fact (on second thoughts) I'm not quite sure what would count as "correct" output for a forecast for z based on an ARIMA model for y.  However, if you're so inclined you can now (you'll need CVS or the current Windows snapshot) do this piece of trickery: <script> open data9-7 arma 1 1 ; QNC matrix b = $coeff set initvals b set bfgs_maxiter 0 arma 1 1 ; STOCK --opg series yh2 = $yhat </script> The essential ingredient is "set bfgs_maxiter 0" (newly permitted), which prevents the BFGS maximizer from making any changes in the coefficients given via "set initvals".  This gives you a "fake" ARMA model for any variable you like using the exact coefficients from some reference model. Note that the --opg flag is required to avoid getting an error: the default is to calculate standard errors using the Hessian, but that will be a big mess in such a case. Allin Cottrell _______________________________________________ Gretl-users mailing list Gretl-users(a)lists.wfu.edu http://lists.wfu.edu/mailman/listinfo/gretl-users