Using the FLjjm package | Loading jjms outputs | Running jjms | jjms.sa | Observation Error Model (oem) | Indices of abundance to generate in MP: | Example / Workflow 1 | Example / Workflow 2 | Reference | buildjjmdata | buildFLIsjjm | FLIndex | More information | Software Versions | Author information | References

Main assumptions and input data for SPiCT | Checklist for the acceptance of a SPiCT assessment | Optional model and assessment tuning | Management based on an accepted SPiCT assessment | References

Introduction | Basic principles | Moving from FLash to FLasher | Where to start

Introduction | Basic principles | Moving from FLash to FLasher | Where to start

Installation | Using read functions to load SS3 results | FLStock | Loading a full OM grid using load | Flow of information SS3 - FLR | Tested SS models | Checking an operating model | Auxiliary functions

Basic functionality | Getting started | Loading built-in example data | Plotting data | Advanced data plotting | Fitting the model | Interpreting summary of results | Interpreting plots of results | Residuals and diagnostics | Process residuals | Extracting parameter estimates | Extracting correlation between parameter estimates | Comparison plots | Advanced functionality | Retrospective plots | Estimation using two or more biomass indices | Using effort data instead of commercial CPUE | Scaling the uncertainty of individual data points | Simulating data | Annual data | Seasonal data | Estimation using quarterly data | Setting initial parameter values | Checking robustness to initial parameter values | Phases and how to fix parameters | Priors | Default priors and how to disable them | Setting a prior | Priors on random effects | Setting priors on the standard deviation of multiple indices | Fixing parameters using priors | Pitfalls when fixing parameters and specifying priors | Robust estimation (reducing influence of extreme observations) | Forecasting and management scenarios | Forecasting | Management | Assessment and intermediate period | Custom management scenarios | Variable management periods | Advanced management settings and functionality | Other model settings and options | catchunit - Define unit of catch observations | dteuler and eulertype - Temporal discretisation and time step | msytype - Stochastic and deterministic reference points | do.sd.report - Perform SD report calculations | reportall - Report all derived quantities | optim.method - Report all derived quantities | References

license: Creative Commons Attribution-ShareAlike 4.0 International Public License | Inputs | Performance levels across MPs | Time series of results of MP runs | Time series of OM history | Standard IOTC MSE plots | plotBPs, indicators boxplots | plotTOs, trade-off plots | kobeMPs, performance on Kobe plot | kobe2MPs, | plotOMruns, time series of OM and MPs | IOTC MSE output tables | perftable | fullperftable | References

Introduction | The operatingModel class | The biological stocks | The fisheries | The projection control | Examples of operating models | The projection process | Calculating the fishing mortality | Projecting the fisheries | Differences with FLash concerning catch weights at age | Projecting the biology | Calculating survivors | Recruitment | Calculating SRP | The timing of spawning | Timing of SRP and recruitment | The SRR parameters and the timing of recruitment | Recycling SRR parameters | Multiple recruitment events | Projection targets | Target types | SRP X | Biological targets | Fbar targets | Internally | get_target_value() | get_target_value_hat() | eval_om() | References

Introduction | The operatingModel class | The biological stocks | The fisheries | The projection control | Examples of operating models | The projection process | Calculating the fishing mortality | Projecting the fisheries | Differences with FLash concerning catch weights at age | Projecting the biology | Calculating survivors | Recruitment | Calculating SRP | The timing of spawning | Timing of SRP and recruitment | The SRR parameters and the timing of recruitment | Recycling SRR parameters | Multiple recruitment events | Projection targets | Target types | SRP X | Biological targets | Fbar targets | Internally | get_target_value() | get_target_value_hat() | eval_om() | References

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Example model fit | Prediction skill by hindcasting cross-validation | Runs test | More information | Software Versions | Author information | References

Introduction | Background / Methods | Using the FLPKG package | Example / Workflow 1 | Example / Workflow 2 | More information | Software Versions | Author information | References

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