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YFT 2023 Grid

Download YFT 2023 assessment report:

Download YFT 2023 diagnostic model:

Download YFT 2023 grid results:

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 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 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.

See also Section 6.2.3 and Table 5 in the YFT 2023 stock assessment report.

The script requires the FLR and FLR4MFCL packages:

install_github("flr/FLCore")
install_github("PacificCommunity/FLR4MFCL")