Certainly not Sir! (grinning)
Nevertheless, how I test the joint significance of the regressors?
Wald test? Or there isn't exist any phenomenon of testing the joint
significance after quantile regressions.
Haider
----
> Exactly what I expected, if CLRM means what I guess it means.
> But if so, why do you expect the F test to still work?
>
> Niels Bohr had a story of a physicist who had a horseshoe
> over his door for good luck, but said -- when reproached
> for superstitious nonsense -- "I've been told
> that it works even if you don't believe in it."
> Is that your position?
>
> Nick
> [email protected]
>
> M. Haider Hussain
>
> Errors were non-normally distributed, that's why I'm using -qreg-. In
> other words, I'm not prepared to enforce CLRM assumptions.
>
> Haider
> Social Policy and Development Center
> Karachi, Pakistan.
>
> > What model is this based on? Gaussian/normal
> > errors? If you are prepared to buy that, why
> > are you doing -qreg-?
> >
> > Nick
> > [email protected]
> >
> > M. Haider Hussain
> >
> > > After running bootstrapped quantile regression with k=15, n=5401, I
> > > obtained Pseudo R2=0.3161. If I want to compute the joint significance
> > > of the regressors, can I still use the F-test given by
> > >
> > > F=[r2/(k-1)]/[(1-r2)/(n-k)]
> > >
> > > If this isn't the case, what's the measure of joint significance of
> > > the regressors after -qreg- / -bsqreg-?
>
> *
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> * http://www.ats.ucla.edu/stat/stata/
>
--
-----------------------------------------M. Haider HussainResearch
OfficerSocial Policy & Development CenterKarachi,
Pakistan.http://www.spdc.org.pk
*
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