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Code for paper investigating the optimal way to bin composition data in stock assessments.

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The effect of discretizing length on growth estimation in integrated age-structured stock assessments

Monnahan, C.C., Ono, K., Anderson, S.C., Rudd, M.B., Hicks, A.C., Hurtado-Ferro, F., Johnson, K.F., Kuriyama, P.T., Licandeo, R.R., Stawitz, C.C., Taylor, I.G., and Valero, J.L. 2016. The effect of length bin width on growth estimation in integrated age-structured stock assessments. Fisheries Research 180:103-112.

This folder contains:

  • Models, case files, results, plots, and figures from the study.
  • The code necessary to reproduce the study.

To reproduce this study:

  1. Clone this repository into a local folder.

  2. Open the run_simulation.R script in R, set working directory to that folder. Use the devtools install commands to install the correct version of ss3sim and r4ss (9/4/2015 was latest install date, you may want to specify a commit from that day to avoid errors introduced by future commits).

  3. Set the ss3sim executables in the system PATH (see vignette for help). Certain versions of ss3sim do this automatically.

  4. Set the number of cores you would like to use. Run the code in Step 0, including sourcing the startup.R script, and installing whichever packages you need to. The workspace should now be ready.

  5. Run steps 2 and 3, which may take a week or longer and a lot of disk space.

  6. Run step 4 to reproduce plots (not in the paper) and figures (are in the paper.

If you just want to explore the results you can accomplish this by running the load_results.R script (after doing step 4 above). The results are now loaded into the workspace. See the script file for the contents of the files.

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Code for paper investigating the optimal way to bin composition data in stock assessments.

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