Am 15.06.2020 um 03:44 schrieb Allin Cottrell:
On Sun, 14 Jun 2020, Sven Schreiber wrote:
> So maybe power turns around for non-Gaussian scenarios.
Certainly relevant; thanks, Sven. I hadn't twigged that "Test2" is
equivalent to Koenker's robust B-P version. I re-ran my test script with
uniform errors (should probably try some other cases) and found:
* Under H0 the original B-P test is "under-sized": rejects at much less
than 5 percent frequency using alpha = 0.05. The size of the robust
version is roughly right.
* Under my H1, error=0.2*x*uniform(), the original B-P test still
rejects with much higher frequency than the Koenker variant.
Obviously, if the original test were always correctly sized or
conservative _and_ had more power, it would be superior. My suspicion is
that for other kinds of violations of the assumptions it might be
oversized, however. But I don't know this specific literature, so far as
it exists.
cheers
sven