Introduction | Model | New Expression | Modify Data | Select Data & Random Effects | Transformations | Initial Values | nthin | Full Model | Analysis Mode | Analyse | Predictions | Predict | New Data

nlist | nlists | mcmc | list | data frame | term frame

Introduction | chk_ Functions | Overview | Missing Input Checker | ... Checker | External Data Source Checkers | NULL checker | Scalar Checkers | Date or DateTime Checkers | Time Zone Checker | Data Structure Checker | Data Type Checkers | Whole Number Checkers | Factor Checker | All Elements Checkers | Function Checker | Name Checkers | Range Checkers | Equal Checkers | Order Checker | Set Checkers | Class Checkers | REGEX Checker | Quality Checkers (Miscellaneous) | check_ functions | References

Basics | Running roxygen | Basic process: human readable documentation | Basic process: making functions available to users | Learn more

Prediction, then measurement | A small worked run | Analysing observed cost | The shard envelope | Comparing predicted against observed | Recalibrating from the run | Across a design | The loop | See also

Why a declarative scenario? | Stage 1: assemble the data | Generated datasets with ssd_gen() | Stage 2: declare the scenario | Dataset input is the collection | min_pmix is referenced by name | dists is a collection of distribution sets | The ci flag | Stage 3: expand into task tables | Stage 4: run the baseline loop | Next: shards, designs, and the targets pipeline | See also

Why estimate cost? | The cost model | The calibration object | Estimating a scenario | From serial total to wall-time | Recalibrating for your machine | Caveats | See also

Start with a single scenario | Migrate: wrap it in a design | Cache-preserving upgrade | Refine: zoom into one region | Notes | See also

What ssdsims is for | Two tracks | A recommended reading order | A 30-second on-ramp

partition_by and bundle: how tasks group into shards | distset: bundled by default, promotable to the path | Run it single core, over shards | Results match the in-memory runner | Scaling up: the targets pipeline | Combining scenarios into a design | Comparing settings in one design | See also

The cluster template | Step 1 — Map your site's SLURM instructions to the controller | Backend prerequisite — the worker install path | Step 2 — Confirm the mapping with the preflight | Step 3 — Run a minimal first job | Step 4 — Swap in your own scenario | Targeting a non-SLURM cluster (untested) | Shard ↔ SLURM-job packing | See also

The destination objects | Run it locally with a dry run | Extend the same call to Azure on a cluster | Verify the upload, in place | What to pay attention to | See also

Introduction | Example | Objects | Specification | Scalar Elements | Vector Elements | Object Elements | Required and Optional Fields | Converting a Single Object

Exports | Manual exports | Imports | Functions | S3 | S4 | Compiled code

Generics | Classes | Methods | Methods for generics in other packages

Summary | Pipeline overview | Why exact reproduction of the ANZECC & ARMCANZ 2000 guideline input data is not possible | What can be approximated | Filtering approach: concentrationused | Structural differences between the 2000 and 2016 databases | Endpoint harmonisation between 2016 and 2000 | Chemical identifier resolution and CAS parent grouping | cas_parent_lookup | Grouped identifier columns | Chemical identifiers available post-mapping | Reference Data for 2016 Toxicity Values | Reference Resolution Strategy | Coverage | SSD eligibility workflow | 1. Base filters | 2. Test type classification and priority selection | 3. ACR conversion for retained acute records | 4. Geometric mean concentration per species × endpoint | 5. Most sensitive endpoint selection | 6. Minimum species and taxonomic group threshold | 7. Nesting | DGV matching | Purpose | Name-based CAS fallback | DGV matching summary | Remaining unmatched chemicals | References

Purpose | Executable source | Inputs | Method | Step 1 — Extract distinct 2016 endpoint labels | Step 2 — Normalise labels | Step 3 — Two-stage mapping to 2000 codes | Step 4 — Output | Outputs | How the lookup is used in the main pipeline | Outcomes (v2 refined) | Remaining unmapped labels | Notes

Introduction | Goal | chk Functions | 1. chk_ Functions | 2. vld_ Functions | 3. check_ Functions | Using chk | Extending chk | abort_chk()

Introduction | What is the issue | What is the impact on the HCx value? | What can be done? | Bias correction using Cox-Snell method - log-normal distribution | Bias correction using Cox-Snell method - gamma distribution | Recommendations

Enabling markdown support | Basic syntax | Sections and subsections | Inline formatting | Code | Lists | Tables | Links | Images | Function links | Code chunks | Chunk options | Possible problems | Some Rd tags can't contain markdown | Mixing Markdown and Rd markup | Leading white space | Spurious lists

Exporting | The introduction | Title | Description | Details | Required tags | Inputs | Outputs | Examples | Usage

Classes | Fields and active bindings | Methods | Dynamic methods | Opting out

Generics | Classes | Methods

Generics | Classes | Methods

How roxygenize() works | Key data structures | Tags | Blocks | Adding a new .Rd tag | Using your new tag | Creating a new roclet | Custom tags | The roclet | Adding a roclet to your workflow | Conclusion: further extension ideas

See also | Family | References | Aliases | Search | Back references

Multiple functions in the same topic | @rdname | @describeIn | Order of includes | Automatically copy tags | Parameters | Recursive inheritance | Multiple parameters | The dot prefix | Inheriting other components | Documenting ... | Inheriting from other packages | Custom tags | Inline code | Inline Rd code | Child documents | Superseded

Philosophy | Installation | Getting Help | Providing Data | Recruitment | Fit a Bayesian model | Convergence | Summary | Priors | Survival | Predictions | Recruitment by year | Recruitment for a 'typical' year | Recruitment trend | Survival by year for a 'typical' month | Survival by month for a 'typical' year | Population Growth | Multi-Population Analysis | Maximum Likelihood | Understanding bboufit objects | References

Scalars | Vectors | Empty lists | Homogeneous R lists of scalars | Homogeneous JSON objects of scalars | Varying | Object | Data Frames | Object of objects | Column-major format

Introduction | Philosophy | Installing | Getting Help | Inputting Data | Fitting Distributions | Coefficients | Plots | Selecting One Distribution | Averaging Multiple Distributions | Estimating the Fit | Hazard/Protection Concentrations | Censored Data | References

Introduction | Methods | Caste study 1 | Case study 2 | Findings | Conclusions and Recommendations | Session Info

Introduction | Methods | Findings | Recommendations | Session Info

Survival | Recruitment | Population Growth | References

Survival and fecundity rates | Process matrices | Population projection | Group allocation

Survival | Recruitment | Population Growth | References

How can I plot the model averaged fit and the individual fits? | How can I include mathematical expressions in the x-axis label when using ssd_plot()? | Censoring | What is censored data? | How is censored data coded in ssdtools? | What are the current limitations on analyzing censored data?

Updating Reference Data for the Database | Process | Reference File Review Process | Concentration Conversion | Duration Conversion | Trophic Groups | Life Stage Codes | BC Species | Concentration Endpoints

Usage | Changing temperature min and max parameters | Changing rate of change parameters | Removing the time buffer | Removing the gap filling | Process

Goals, and how achieved | Non-goals | Workflow

Updating the Add Data Template | Associated Reference Data | To update the template | Push and install the pacakge

Two Ecotypes | Fish | Stock-Recruitment | Yield

Configure | Run | Reconfigure | Rerun | Clean Up

Beta-binomial distribution | Deviance: | Deviance residuals

Simple lists | Paragraph lists | Nested lists

Heading 2 | A heading with code | Heading 3a | Heading 3b | Heading 4a | Heading 4b | Heading 4c

Simulate survival and fecundity rates | Project population | Allocate and sample groups | Simulate abundance, survival and recruitment data

Introduction | Set up the development environment | Create a package | Create and configure a Git repository | Create initial NEWS.md file | The development phase | Create an R file | Create a test | Update NEWS.md | Review NEWS.md | Finalize version | Change code and commit | Prepare for release | Bump version for release | Generate release notes | After release | Tag version | Create GitHub release | Restart development

Installation & setup | Functions | Full fledge usage | FAQ & edge cases

Implementation | Updating NEWS.md | Collecting NEWS | Tagging for "dev" vs. other releases

Introduction | Growth | Length | Weight | Reproduction | Fecundity | Spawning | Death | Natural Mortality | Fishing Mortality | Recruitment | Yield | Efficiency | References

Running reverse dependencies in the cloud | Setup | Usage

Simulating as nlists Objects | Saving as .rds Files | Importing .rds Files | Adding .rds Files | Copying .rds Files | Checking .rds Files | Parallelization | Progress

Collections | Collection Properties

Batch exporting and importing flobs for an sqlite database | Saving flobs from a database | Importing flobs back into a database | Working with individual tables and columns

Starting | Writing Data | Exists | Foreign Keys | Committing Data | Deleting Data (and Meta Data) | Replacing Data | Duplicate Data | All Data | Strict | Silent | Reading Data | Cleaning Up

Primary Objects | Scalars | Other Objects | Function Functions | Data Functions | Miscellaneous Functions

Package Overview | base | assertthat | checkmate | checkr | Package Comparison | Return Values | Custom Error Messages | Speed | Dependencies

Weight vs Length | Fecundity vs Length | Fecundity vs Weight

Common use | Code block selection | Engine selection | Icon positioning | Color customization | Tooltip messages | Browser Support