Re: Testing the fit of the model

Dear Mekonnen,

The argument to !DENSE is reduced to 5000 if it is given a value greater
than 5000.

If you are wishing to use R-square,
then you must be working with an entirely fixed model.

Consequently, R-squared is RSS/TSS = (TSS-ESS)/TSS
where RSS is regression Sum of sqyares, TSS is Total (corrected) Sum of
Squares
and ESS is Error (Residual) Sum of Squares.

Now EMS=ESS/NEDF and NEDF are reported.
and if you fit the simple model Y ~ mu,
TSS=ESS

so, you could fit all fixed effects as sparse and still calculate
R-square.

Now if the model involves many covariates such that the SSP (Sum of
Squares and Cross products matrix) is effectively dense (few zero
cells), fitting it in ASReml as DENSE rather than SPARSE will be
quicker, even though it will be slow.

   
On Thu, 2009-04-23 at 10:02 +1000, Mekonnen.HaileMariam_at_DPI.VIC.GOV.AU
wrote:
>
> Dear Dr. Gilmour and Asreml users,
> Can one increase the Dense part of the equation to more than 5000
> equations? In the manual the limit is 5000 equations.
> It is sometimes good to fit more fixed effects in the dense when one
> wants to choose a suitable models. It will make the choice of models
> easier if we can get r-square and compare models based on r-square?
> May be one get achieve the same outcomes in other ways?
>
>
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