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

Primary goals | Collaboration | Coding style | Suggested norms - General | Organization | Projects | Example folder structure | Scripts | Structure guide | Style guide | Naming conventions | Object names | Dates | Spacing | Writing functions | Function components | Suggested norms - Specific | Framework | Code framework | Teams framework

Additional functionality | Example script

Setup Model Dimensions | Setup Recruitment Dynamics | Setup Biological Dynamics | Setup Movement and Tagging | Setup Catch and Fishing Mortality | Setup Fishery Indices and Compositions | Setup Survey Indices and Compositions | Setting up Fishery Selectivity and Catchability | Setting up Survey Selectivity and Catchability | Setup Model Weighting | Fit Model and Plot

Define Operating Model | Define Management Options | Define Estimation Model | Define and Run Closed-Loop Simulation

Reference Points | Single Region | Spawning Potential Ratio | Maximum Sustainable Yield (Beverton-Holt) | Multi-Region | Independent | Global | Local | Deriving Catch Advice and Projections | Code Demonstration | Getting Reference Points | Multi Region | Conducting Catch Projections to Derive Catch Advice (Deterministic Recruitment) | Conducting Stochastic Population Projections | References

Overview | Estimation Model | Projection Options | Functions to Determine Catch | Management Procedures | Simulation Loop (Single Replicate) | Simulation Loop (Parrallelized) | Condition Closed Loop Simulation | Run Simulations | Process Results | Visualize

Data Inputs for Defining Model Dimensions | Data Inputs for Defining Recruitment Processes | Data Inputs for Defining Biological Processes | Data Inputs for Defining Movement Processes | Data Inputs for Defining Tagging Processes | Data Inputs for Defining Catch and Fishing Mortality Processes | Data Inputs for Defining Fishery Indices and Compositions | Data Inputs for Defining Survey Indices and Compositions | Data Inputs for Defining Fishery Selectivity and Catchability | Data Inputs for Defining Survey Selectivity and Catchability | Data Inputs for Defining Model Weighting

Process Equations | Population Initialization | Recruitment Processes | Population Projection | Observation Equations | Fishery Observation Model | Survey Observation Model | Tagging Observation Model | Fishery and Survey Selectivity | Likelihoods | Observation Likelihoods | Fishery Catches | Fishery and Survey Indices | Fishery and Survey Compositions | Structuring Compositions and Ageing Error | Tagging | Parameter Priors and Process Error Penalties | Parameter Priors | Natural Mortality | Fishery and Survey Catchability | Steepness | Recruitment Proportions | Movement | Tag Reporting Rates | Process Error Penalties | Initial Age Deviations | Recruitment Deviations | Fishing Mortality Deviations | Joint Likelihood | References

Simulation Settings | Population, Recruitment, and Biological Processes | Fishery Processes | Survey Processes | Tagging

Setup Model Dimensions | Setup Recruitment Dynamics | Setup Biological Dynamics | Setup Movement and Tagging Dynamics | Setup Catch and Fishing Mortality | Setup Index and Composition Data (Fishery and Survey) | Setup Selectivity and Catchability (Fishery and Survey) | Setup Model Weighting | Fit Model and Plot

Simulation Cross-Testing in SPoRC | Define Model Dimensions | Fishing Processes | Survey Processes | Biological Dynamics | Tagging and Movement | Recruitment | Run the Operating Model | Define Estimation Model | Run Cross-Test Analysis | Self Testing

Load data and packages | Setup model | Setup Recruitment Dynamics | Setup biological dynamics | Setup Movement and Tagging | Setup Catch and Fishing Mortality | Setup Fishery Indices and Compositions | Setup Survey Indices and Compositions | Setup Fishery Selectivity and Catchability | Setup Survey Selectivity and Catchability | Setup Model Weighting | Fit model | Fit model (Without Francis) | Fit model (With Francis) | Check Model Results | Convergence | Time Series Results | Catch and Index Fits | Composition Fits | Fishery Ages | Fishery Lengths | Survey Ages | Retrospectives | Retrospectives (Without Francis) | Retrospectives (With Francis) | Likelihood Profiles | Jitter Analysis | MCMC | Reference Points and Projections | Reference Points | Projections | Spawning Biomass Projections | Catch Projections | Catch Advice under $F_{40%}$ | Fishing Mortality Projections

Fishery Removals | Fishery Selectivity | Fishery Catchability | Fishery Composition Likelihoods | Survey Selectivity | Survey Catchability | Survey Composition Likelihoods | Natural Mortality | Recruitment | Movement | Tagging

Biological Processes | Fishery Processes | Survey Processes | Tagging Processes | Likelihoods | Parameter Deviations | Derived Quantities

Setup Model Dimensions | Setup Recruitment Dynamics | Setup Biological Dynamics | Setup Movement and Tagging Dynamics | Setup Catch and Fishing Mortality | Setup Index and Composition Data (Fishery and Survey) | Setup Selectivity and Catchability (Fishery and Survey) | Setup Model Weighting | Fit Model and Plot

Starting Values | Mapping | Fixing Parameters | Sharing Parameters

Steepness | Natural Mortality | Catchability | Selectivity | Movement | Tag Reporting Rates | Recruitment Proportions

afscISS::get_ISS() | afscISS::get_popn() | afscISS::get_comp() | afscISS::get_bias()

Loading & viewing your data | Detecting Breakpoints | Re-fitting growth curves at putative breaks | Updating and re-fitting the breakpoints

Base model structure for a single survey and stratum | Extending to multiple biomass survey strata | Addition of an auxiliary catch per unit effort (CPUE) survey | The ADMB version of REMA | Estimation of additional observation error | Exploration of the Tweedie distribution for zero biomass observations | Experimental One-Step Ahead (OSA) residuals | References

Background | A testing framework for REMA model validation | Prepare data for each stock here | 1. Simulation self-test: Can we recover parameters without bias? | 2. Residual analysis | 3. Laplace approximation: Are the model assumptions related to random effects estimation reasonable? | 4. Parameter correlation: Are the model parameters identifiable and non-redundant? | Results of parameter correlation analysis | 5. Is the GOA Thornyhead model really converged? | When should we care about failed model diagnostics? | Preliminary recommendations | References

Model 1: Zeros as NAs | Model 2: Add a small constant | Model 3: Tweedie distribution | Compare model results

EBS Pollock Model Description | Dynamics | Recruitment | Diagnostics | Parameter estimation | Uncertainty in mean body mass | Tier 1 projections

Example use of ebswp library for setting up a new model | Read in an existing model | For SSB1 | And SSB2 | And obs-error run | Now run them all in parallel

Example

Model 1: Fit to the biomass and CPUE survey through the estimation of a scaling parameter $q$ | A comparison of the ADMB and TMB models | Model 2: Estimating additional observation error in the two surveys | Model comparison | Model selection | Apportionment results

The rema workflow: | Example 1: Univariate random effects (RE) model with a single survey and stratum | Example 2: Multivariate random effects model (REM) with a single survey and multiple strata

Let's make a plot!