Dear SS Experts,
First of all, sorry for asking too many questions, but we are working
on improving our SS model for hake, and in this process many doubts
and questions arise.
We are currently experimenting with the lambda parameter to control
the contribution of each data source to the total likelihood. During
this process, we have been reviewing the table of likelihood values
(see image) and have noticed some points that we don't fully understand:
For example, in the case of catches, the likelihood value in the
table correspond to the sum of the "Like" column from the
catch information table (which we understand contains the -log L for
each observation). This makes sense to us.
However, for other components such as surveys or discards, we observe
something different. Specifically, the likelihood value for the
indices in the likelihood table is -79.5787, and does not correspond
to the sum of the 'Like' column in the indices table. Instead, it
corresponds to the sum of the "Like" column plus log(SE).
The resulting value changes significantly from 112.1084 to -79.5787
when log(SE) is added.
We do not understand why the "Like" column, which we
interpret as -log(L), is modified by adding log(SE) for components
such as discards or surveys. This additional term seems to change the
contribution of these components to the total likelihood significantly.
We would be very grateful if you could explain the rationale for
adding this term.
Thank you very much for your time and help!
