[Gretl-users] Re: gretl development roadmap

[Ignacio Díaz-Emparanza]

El Viernes, 15 de Julio de 2005 02:44, Allin Cottrell escribió:
>...
>
> As for forecasting, that's now pretty much done in the latest
> release.  In gretl CVS we have seasonal ARMA and considerably
> enhanced support for VARs.  We don't yet have a serious start on
> user-defined matrix manipulation, though many of the required basic
> functions are there in gretl_matrix.c.
>
> More generally, the question is, what level of sophistication is
> gretl aiming for?  My original idea (as I recall) was that I wanted
> gretl to be an excellent tool for undergraduate-level econometrics.

In 2001 I was several months looking for an econometrics package I could offer 
to my undergraduate students for free. I was just discovering "open source" 
and Linux, and I was really surprised when I found Gretl. I liked the 
structure of gretl just when I saw it, mainly because of its so user-friendly 
interface. The Windows version of gretl was full of bugs, so I began to 
collaborate sending very long reports of bugs. Now I think we have reached an 
stage in which gretl is very stable and very appropiate for teaching 
Econometrics in an undergraduate level. It covers now almost all the 
undergraduate programs we teach at our University. (With the seasonal ARMA, 
it will also cover the programs of the "Time series" subjects, thank you 
Allin).

> I think we've pretty much got there, but the target has moved.
> I think the notion is: If gretl provides a good interface for doing
> econometric work, why stop at the basics?  The value of gretl, even
> to undergrads, will be enhanced if they can continue to use this
> program for professional work.

I do not agree with Allin at this subject. Postgraduate econometrics work 
usually requires programming at a very specific level. We have a lot of 
computer "languages" for doing econometrics at this specific level now: 
Gauss, Rats (including the compile mode), Ox, Splus, R, Octave, ...
I  the 90's I was a Rats user, and when I discovered the "open source" 
philosophy, I thought in porting some of my programs to an "open source" 
language. 

R is a  language and environment for statistical computing and graphics (see 
http://www.r-project.org ) which is, as gretl,  "open source and free 
software", has a very strong user community, a very structured development 
team, and a quality control that ensures that the published packages 
(libraries and functions) has a very low probability of errors.

I think we should not dedicate much effort in adding new features to the gretl 
console, but it will be better for the user to get a better relation with the 
R language. At present, we can open a dataset in gretl and through 
"Utilities/Start Gnu R" we can open an R session and read our dataset. It is 
very usefull, because now we can operate with these data with all the 
commands and functions of R. But now we would need a way to recover some of 
the R results (yhats, residuals, coefficients, ..) passing them again to 
Gretl. 

Having this type of link gretl<-->R working, we will avoid the necessity to 
program all the features that are already programmed in R. For example, 
suppose you need to use the Kalman filter, Structural Time Series Models, or 
whatever matricial operation, all of these can be done in R (reading the 
manuals, of course).

I think Gretl and R are now complementary programs. Gretl for the basics and R 
for the advanced econometrics. Increasing the capabilities of the gretl 
console (gretlcli) will lead also  the user "to look everything up in the 
docs before he can work with data". 
We should avoid that the user have to learn two different "languages" for 
doing the same things (in R and gretl), and so we should avoid that gretl and 
R compete for the users.

>
> I'll try to summarize:  My (immodest) notion is that gretl should be
> an extremely user-friendly econometrics (and to some extent, general
> statistics) package with true cross-platform GUI functionality and
> also solid support for scripting.  It should be a flagship for
> free, open-source software in the statistical domain -- a program
> which many users might prefer to expensive proprietary alternatives
> (I have some evidence that this is true already).

I agree with almost all above. I only suggest that we should not define 
another scripting language very different from the existing ones (specially 
from the R language).



-- 
Ignacio Díaz-Emparanza
Dpto. de Economía Aplicada III (Econometría y Estadística)
UPV-EHU
http://www.bl.ehu.es/~etpdihei/