Comments (2)
@iantaylor-NOAA
Heads up for r4ss. The _Mgmt_Quantity report already shows Recr_Unfished. I want to add Recr_SPR, Recr_Btgt, and Recr_MSY as part of the expanded output associated with understanding how spawner-recruitment interacts with time-varying biology.
from ss3-source-code.
No problem. The only place I see that makes a difference would be in the time series plot where it filters to get the standard deviation of the year-specific derived quantities and previously excluded "Recr_Unfished" specifically. I've just changed that in r4ss commit 1c22a4d, so it will exclude anything which doesn't have a numerical value after the "Recr_".
I agree that the additional quantities could be helpful and good to have in the table.
from ss3-source-code.
Related Issues (20)
- [Feature]: add discard body weights to wtatage.ss
- [Refactor]: create function for t=f(y,s)
- Extending time-blocks into forecast years HOT 1
- refactor Fmethod controls and expand Fmethod 4 capabilities
- [Feature]: 10+ multiyear average F_std_scaling; with change to log(ratio) approach HOT 3
- [Feature]: Revise recdev_bias adjustment to be a customizable list of line segments
- [Bug]: Possible bug relating to the estimation of Q_extra_SD when doing NUTS MCMC HOT 10
- [Feature]: Mean recruitment adjustment HOT 10
- [Feature]: Add 2-parm catchability (Q) option with offset and slope HOT 2
- [Feature]: add link to artifact of exe build to pull request discussion?
- [Bug]: "inf" value in bootstrap of mean size-at-age data for ages with sample size 0
- [Feature]: Cohort growth deviation added to Linf (or L2) HOT 1
- Add more detail for "catches" warning HOT 1
- [Feature]: One step ahead (OSA) residuals for composition data
- [Bug]: Time_Series output of forecast recruitment in a seasonal model HOT 1
- revise SPR_SERIES in Report.sso to clarify HOT 5
- revise RECR_DIST output to work better for models without 50/50 sex ratio at recruitment? HOT 2
- [Feature]: consider adding more stock-recruit functions HOT 1
- [Bug]: rho parameters not impacting semi-parametric (2D-AR) selectivity when multiple sigma values are used HOT 2
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