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
.
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.
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.
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},
#> }
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