Am 23.03.2017 um 19:05 schrieb Allin Cottrell:
1) The convention when calculating BIC from a model estimated by least
squares is to set "k" to the number of regression coefficients (leaving
aside the error variance), while the convention under MLE is to include
the variance estimator in k. (Or at least I think that's a fair
statement of the case.)
One more follow-up here: Can you give a source for the convention? I
guess in principle one can make the case that also the error variance
could be fixed a priori and not estimated, and so k should change
accordingly. But right now I don't see why that argument wouldn't apply
to OLS as well.
(Or are there some block-diagonal and/or asymptotic independence
arguments that would apply to one estimator here and not the other?)
thanks,
sven