On Sun, 23 Nov 2008, Riccardo (Jack) Lucchetti wrote:
On Sat, 22 Nov 2008, Allin Cottrell wrote:
>> So, could the following (Allin's proposal with the adj. R^2 and the
>> F-statistic swapped) be a reasonable compromise?
>>
>> Sum squared resid 59.23226 Mean dependent var 2.962500
>> S.E. of regression 0.473671 S.D. dependent var 0.615864
>> R-squared 0.419454 Adjusted R-squared 0.408459
>> F(5, 264) 38.14888 P-value(F) 2.14e-29
>> Log-likelihood -178.3244 Akaike criterion 368.6488
>> Schwarz criterion 390.2393 Hannan-Quinn 377.3186
>> rho 0.435670 Durbin-Watson 2.036421
>
> I like it!
Anyone who doesn't? Speak now or forever hold your peace.
Well... third thoughts! There are quite a few contexts in which
we print somewhat modified regression statistics (for example, for
WLS or AR1 estimation). I presume it's desirable that we handle
as many such cases as we reasonably can in a manner consistent
with plain OLS results. And in that regard it's easiest if we go
all the way with your row-wise presentation. For instance, it's
handy to be able to skip a single row containing the mean and s.d.
of the dependent variable. So here's an example of what I'm
working with at present:
Mean dependent var 4.538837 S.D. dependent var 0.243346
Sum squared resid 1.617235 S.E. of regression 0.189575
R-squared 0.430985 Adjusted R-squared 0.405696
F(2, 45) 17.04203 P-value(F) 3.09e-06
Log-likelihood 13.26255 Akaike criterion -20.52509
Schwarz criterion -14.91149 Hannan-Quinn -18.40371
rho 0.018627 Durbin-Watson 1.960299
(with the last row omitted for non-time series).
Allin.