https://github.com/pacificcommunity/ofp-sam-yft-2023-grid
YFT 2023 Grid
https://github.com/pacificcommunity/ofp-sam-yft-2023-grid
2023 assessment ofp sam yft
Last synced: about 2 months ago
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YFT 2023 Grid
- Host: GitHub
- URL: https://github.com/pacificcommunity/ofp-sam-yft-2023-grid
- Owner: PacificCommunity
- Created: 2023-07-25T05:30:40.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-10T01:36:08.000Z (6 months ago)
- Last Synced: 2024-12-10T02:27:20.678Z (6 months ago)
- Topics: 2023, assessment, ofp, sam, yft
- Language: Shell
- Homepage:
- Size: 7.15 MB
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# YFT 2023 Grid Results
Download YFT 2023 assessment report:
- **Stock assessment of yellowfin tuna in the western and central Pacific Ocean: 2023**\
**[WCPFC-SC19-2023/SA-WP-04](https://meetings.wcpfc.int/node/19352)**
Download YFT 2023 diagnostic model:
- Clone the **[yft-2023-diagnostic](https://github.com/PacificCommunity/ofp-sam-yft-2023-diagnostic)** repository or download as **[main.zip](https://github.com/PacificCommunity/ofp-sam-yft-2023-diagnostic/archive/refs/heads/main.zip)** file
Download YFT 2023 grid results:
- The **[yft-2023-grid](https://github.com/PacificCommunity/ofp-sam-yft-2023-grid)** repository includes a **[yft-2023-grid-results.zip](https://github.com/PacificCommunity/ofp-sam-yft-2023-grid/releases/download/file/yft-2023-grid-results.zip)** file
## Grid of ensemble models
The YFT 2023 assessment used a structural uncertainty grid with 54 models:
Axis | Levels | Option
------------------- | ------ | -----------------------------------
Tag mixing | 2 | 1, 2* quarters
Size data weighting | 3 | Sample sizes divided by 10, 20*, 40
Age data weighting | 3 | 0.5, 0.75*, 1
Steepness | 3 | 0.65, 0.80*, 0.95
## Grid results
The [yft-2023-grid-results.zip](https://github.com/PacificCommunity/ofp-sam-yft-2023-grid/releases/download/file/yft-2023-grid-results.zip) file contains all files necessary to run or browse the YFT 2023 grid models.
The grid models are run from a par file, as described in the corresponding `doitall.sh` script. This starting par file is the best of 20 jittered par files from the pre-grid analysis.
The final par and rep files are consistently named `final.par` and `plot-final.par.rep` to facilitate harvesting results from across the 54 grid member models.
Preview of zip file contents:
```
yft-2023-grid-results.zip
├── bin
│ └── mfclo64
└── grid
├── m1_s10_a050_h65
│ ├── 13.par
│ ├── 14.par
│ ├── dohessian_standalone.sh
│ ├── doitall.sh
│ ├── final.par
│ ├── mfcl.cfg
│ ├── neigenvalues
│ ├── plot-final.par.rep
│ ├── test_plot_output
│ ├── xinit.rpt
│ ├── yft.age_length
│ ├── yft.frq
│ ├── yft_hess_inv_diag
│ ├── yft_pos_hess_cor
│ ├── yft.tag
│ └── yft.var
├── m1_s10_a050_h80
│ ├── ...
```
## Incorporating structural and estimation uncertainty
The [estimation_uncertainty.R](notes/estimation_uncertainty.R) script uses Monte Carlo simulations to add estimation uncertainty to the structural uncertainty grid estimates of reference points. The resulting means and quantiles are found in [estimation_uncertainty.csv](notes/estimation_uncertainty.csv).
See also Section 6.2.3 and Table 5 in the YFT 2023 stock assessment [report](https://meetings.wcpfc.int/node/19352).
The script requires the FLR and FLR4MFCL packages:
```
install_github("flr/FLCore")
install_github("PacificCommunity/FLR4MFCL")
```