On Fri, 8 Jul 2016, Sven Schreiber wrote:
I'm getting "data errors" in a situation where the
various series in the
dataset have different extents of missing values in them (only at the end or
the beginning, so no gappy series [I think]) and I do "omit --auto=0.1".
The errors go away when I precede the estimation and omit commands with a
"smpl ... --no-missing" line, that's why I think it has to do with the
Right now I don't have time to cook up a concrete example, but I could try
later if this information isn't enough. This is with gretl 2016c on Windows.
An example would be good. I tried cooking up the following, on a
dataset with n = 51.
INCOME = NA
ols 1 0 2 3 4 5 6 7 8 9
Here no series have any NAs before I stuck one in for INCOME, which
I chose because it's the first candidate for omission from the
kitchen-sink model (P-value 0.7486). So in principle after dropping
INCOME gretl could estimate the first reduced model using n=51 (as
opposed to n=50 for the full model), which would then yield an
invalid comparison and so (hopefully) trigger an error.
However, what actually happened was that gretl kept the original
n=50 sample as established by the initial OLS: it's not fooled so
easily. I tried setting INCOME to NA also, for good measure, but
it's the same story: gretl sticks with the sample defined by the
So what you're describing must be something more subtle.