Re: [Gretl-devel] Report
On Tue, Feb 28, 2012 at 10:19 PM, Allin Cottrell <cottrell(a)wfu.edu> wrote:
On Mon, 27 Feb 2012, Talha Yalta wrote:
> 1)- Some people were very much interested in the principal components
> functionality but they were ultimately disappointed. Apparently they
> need to use this functionality (in SPSS) to create various indexes
> using a large number of series. Still, I guess this can be considered
> more like a statistical functionality than an econometric one, no?
What in particular didn't they like about gretl's "pca"
command (and/or the princomp() function)? What's missing from
their point of view?
These people were from State Planning Agency. They told me
that they
have about 60 series (which have different levels of collinearity) and
they use SPSS to do principal components analysis to create regional
development indices (Turkey has 81 provinces). I am not very familiar
with pca but I can call them and learn more.
> 2)- Some students suggested (and all others agreed) that it would
be
> very useful to have a predict command, which will provide predicted
> values as well as slopes (given Xs) for various nonlinear models such
> as polynomial regressions, logit, probit etc. I think this could be
> nice to have as a command as well as a GUI entry next to the forecast
> item. Maybe a small goodie to consider for the 2.0 release? They said
> Stata has this.
I don't see what the difference is between "predicted values"
and what we offer already (in sample fitted values and
out-of-sample forecasts). Can you expand on what you mean?
Now this is maybe I
didn't know how to fully use gretl in this
context. The issue arised on 2 occasions:
(1) I had a polynomial regression and I was showing them to enter from
the GUI the command something like:
prediction = $coeff[1] + $coeff[2]*x + $coeff[3]*x^2
(2) I was showing an ordered logit example and I had long commands like:
pcut0 = 1 / (1+exp(-$coeff[1]-x*$coeff[2])+exp(-$coeff[1]-x*$coeff[3]))
pcut1= exp(-$coeff[1]-x*$coeff[2]) /
(1+exp(-$coeff[1]-x*$coeff[2])+exp(-$coeff[1]-x*$coeff[3]))
pcut2= exp(-$coeff[1]-x*$coeff[3]) /
(1+exp(-$coeff[1]-x*$coeff[2])+exp(-$coeff[1]-x*$coeff[3]))
...and they said Stata (supposedly) has a command where you enter x
and get the prediction and slope for different models :-P
I think that one should be disabled too, leaving the plain
"Close" option.
Yes this is probably the best. Thanks for the fix.
Sincerely
Talha
--
“An expert is a person who has made all the mistakes that can be made
in a very narrow field.” - Niels Bohr (1885-1962)
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