[feat]: get index error distribution from SS3 models #471

Is your feature request related to a problem? Please describe.

Thanks to @ericward-noaa for adding index intervals in #468. This is an important feature that is important to be able to interpret the index fits.

One refinement needed in the future is to account for the fact that SS3 has multiple options for error structure for indices:

• -1=normal;
• 0=lognormal;
• 1=lognormal with bias correction;
• >1=df for T-distribution

Of these, lognormal probably covers at least 95% of models, but the normal error is used for models that include an environmental predictor of recruitment deviations.

The plot below was created loading stockplotr from Eric's fork associated with #468 and running the following code which relies on a petrale sole model with an index of recruitment deviations posted by @okenk. The "env" fleet uses normal error since the index spans zero so the intervals should be symmetric around the points and not tiny for observations close to zero.

petrale <- r4ss::SS_output('https://raw.githubusercontent.com/okenk/recruit_index_sims/refs/heads/main/simulations/petrale/0.2_30/30/em/')
petrale_converted <- convert_output(petrale)
plot_index(petrale_converted, interval = 0.95, module = "cpue")

Describe the solution you would like.

I don't think that convert_output() is currently getting the information on error structure. In Report.sso that's in a separate table from the main table of index output.

Currently, r4ss::SS_output() returns the table $cpue (which is converted and serves the basis for the plots) as well as two vectors $survey_units (which is probably not needed for plotting), and $survey_error, which contains the codes above.

I'm happy to modify r4ss::SS_output() to merge those vectors into $cpue so that units and error were just additional columns. These would then need to be somehow integrated into the table created by convert_output(), ideally in a format that is similar to what FIMS will use to store index error structure assuming that in the future there will be additional uncertainty options beyond the current ~ dlnorm() option.

Describe alternatives you have considered

stockplotr::convert_output() could also do the merging of the separate SS3 tables

Additional context

No response