We have also seen how to recover well known formulas, obtained starting from other approaches, under well defined conditions, thus indicating that other methods can be seen as approximations of the most general one, and that are therefore applicable if the conditions of validity hold.

The linear case with errors on both axis and extra variance
of the data has been shown with quite some detail,
giving un-normalized formulas for the pdf. In particular,
going to the pretext to write this paper, we can see that
Eq. (43) of Ref. [17] is not reproduced.
In fact, if I understand it correctly, that equation should have the
same meaning of Eq. (53) of this paper.
However, Eq. (43) of Ref. [17] contains
an extra factor (using the notation of this
paper), that it is a bit odd, for several reasons
(besides the fact that I do not get it - but this could be
judged a technical argument by the hurry reader).
The first reason is just dimensionality:
is
homogeneous with
and for this reason
can be combined (quadratically) to ,
but cannot be added *tout court* to 1.
The second is that if there was such a factor in Eq. (53),
then one cannot reproduce Eqs. (58),
(60) and (61),
that one can be obtained in simpler ways (and that give rise to the
likelihoods shown in Section 6,
some of them rather well known).
Note that the addition of a term in
Eq. (53) has the net effect of overestimating ,
an effect that is consistent with the claim by [1]
of a slope larger than that obtained by
[14].^{8}