Overview | Creating plots | Example: Creating plots from simple and adding a custom tab | read model output | make the default plots and associated HTML files | Make custom plots and write CSV file with info about them | Add custom plots to the .csv | Getting the plots onto github

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 | Prerequisites | Print, sort and summary of RDBESDataObject | Sorting RDBESDataObject | Combining RDBESDataObjects | Filtering RDBESDataObjects | Getting Subsets of RDBESDataObject Tables

Introduction | Load the package | Importing zipped files | Importing csv files | Importing list of data frames | Object class RDBESDataObject | validate RDBESDataObject

Introduction | Load the package | main data requirements to generate probabilities | Load and validate some example data | A closer look at the example data | generating probabilities for only one table: generateProbs | generating probabilities for an entire RDBES data object: applyGenerateProbs | The overwrite argument

Introduction | Load the package | Load and validate example data | A closer look the example data and its characteristics | Generating Zeros for species looked for but not reported in the SA table

Introduction | Load the package | Load and validate example data | A closer look the example data and its characteristics | Generating NAs for species not looked for | Dealing with diligent observers

Introduction | Load the package | Prerequisit | A closer look into the example data and its characteristics | Rename species code in SA table using SL table.

Introduction | Prerequisites | Single level Multiple Count Estimator | Estimation workflow | Estimation on Multiple Strata | Two Level Estimation on Single Stratum

Introduction | Prerequisites | Estimation workflow | Simple Estimation Example

Introduction | Load the package | Step 1) load and prepare some test data | Step 2) Estimate for live weight for the data | Step 3) Export the results to InterCatch format (just HI and SI for this data)

Dependency Network | Visualization | Table

Introduction | Installation of mixfishtools | Mixed fisheries considerations | Headline plot of catch uptake by stock and scenario | Fleet effort restriction plot | Landing by stock plot | Landing by metier and stock plot | Other plotting functions | Catch composition | Plot catch composition for each fleet over time | Plot landings composition for each area by country-metier combinations | Plot landings composition for each metier by country for single year | Over-/under-quota plot | Catch alluvial plot

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

Vignette change log | cat3advice R package | Documentation | Installation | Tutorial | The rfb rule | Reference catch $A_y$ | Biomass index trend (ratio) $r$ | Biomass safeguard $b$ | Fishing pressure proxy $f$ | Length data | Length at first capture $L_c$ | Mean length | Reference length | Indicator | Multiplier $m$ | Application of rfb rule | The rb rule | Application of rb rule | The chr rule | Biomass index value $I_{y-1}$ | Target harvest rate $HR_{\text{MSYproxy}}$ | Harvest rate | Harvest rate target $HR_{\text{MSYproxy}}$ | Application of chr rule | chr rule with custom parameters and discard survival | Data | Biomass index value | Target harvest rate | Biomass safeguard | Multiplier | Application of the (tuned) chr rule | References

Introduction | General FLStock creation | Age-based stocks | Direct extraction from SAM using FLfse | Quality control checks | Biomass-based stocks with dynamics | Fixed stocks without dynamics (e.g. Nephops) | Direct setup through manual entry | Indirect setup through import | Other considerations for Nephrops FUs without survey estimates | Requested stocks | Stock specific requests | Software Versions

Introduction | The procedure | The FLStock with assessment summary | Extend FLStock for short-term forecast | Define forecast control | Run deterministic forecast with FLasher | Compare summary statistics | Typical problems | Special case: fixed dynamics and harvest rate advice (Nephrops) | Software Versions

Installing the r4ss R package | Basic installation | Loading the package and reading help pages | Alternative versions | Reading model output and making default plots | Creating select plots | Scripting Stock Synthesis workflows with r4ss | Read in Stock Synthesis files | Investigate the model | Modify the model | Write out the modified models | Download the Stock Synthesis executable from GitHub | Run the modified model | Investigate the model run | Should I script my whole Stock Synthesis workflow? | Functions for common stock assessment tasks | Running retrospectives | Jittering | Tuning composition data

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

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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