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R package with advanced diagnostics to evaluate a Stock Synthesis model. Diagnostics include residual analyses, hindcasting and cross-validation techniques, and retrospective analyses.

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PIFSCstockassessments/ss3diags

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ss3diags

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The R package ss3diags enables users to apply advanced diagnostics to evaluate a Stock Synthesis model. Diagnostics include residual analyses, hindcast cross-validation techniques, and retrospective analyses. Functions also allow users to reproduce the key model diagnostics plots that are presented in the paper ‘A Cookbook for Using Model Diagnostics in Integrated Stock Assessments’ (Carvalho et al. 2021).

The ss3diags Github repository provides step-by-step R recipes on how to:

with Stock Synthesis by making use of a comprehensive collection of R functions available in the R packages r4ss and ss3diags.

Installation

ss3diags is not currently supported on CRAN. You can install the development version of ss3diags from GitHub with:

# install.packages("remotes")
remotes::install_github("PIFSCstockassessments/ss3diags")

Once the package is installed it can be loaded by:

library(ss3diags)

For examples of how to run common diagnostic tests for SS models and visualize the results of those diagnostic tests using the r4ss and ss3diags packages, please refer to the articles on the package website.

Contributing to ss3diags

If you would like to contribute to ss3diags or have suggestions for diagnostic tests to include in the package, you can submit a new issue or email Meg at megumi.oshima@noaa.gov.

Reference

To cite ss3diags for a publication you can use

citation("ss3diags")
#> To cite package 'ss3diags' in publications use:
#> 
#>   Winker H, Carvalho F, Cardinale M, Kell L, Oshima M, Fletcher E
#>   (2023). _ss3diags: Stock Synthesis Model Diagnostics for Intergated
#>   Stock Assessments_. R package version 2.1.1,
#>   <https://github.com/PIFSCstockassessments/ss3diags>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {ss3diags: Stock Synthesis Model Diagnostics for Intergated Stock Assessments},
#>     author = {Henning Winker and Felipe Carvalho and Massimiliano Cardinale and Laurence Kell and Megumi Oshima and Eric Fletcher},
#>     year = {2023},
#>     note = {R package version 2.1.1},
#>     url = {https://github.com/PIFSCstockassessments/ss3diags},
#>   }

Disclaimer

The United States Department of Commerce (DOC) GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. DOC has relinquished control of the information and no longer has responsibility to protect the integrity, confidentiality, or availability of the information. Any claims against the Department of Commerce stemming from the use of its GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.”

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R package with advanced diagnostics to evaluate a Stock Synthesis model. Diagnostics include residual analyses, hindcasting and cross-validation techniques, and retrospective analyses.

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