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@ss3sim

ss3sim

NOAA Fisheries

Overview

In this organization you can find repositories associated with {ss3im}, an R package that simplifies the steps needed to generate beautiful simulation output from the widely-used Stock Synthesis (SS3). SS3 is a statistical age-structured stock assessment framework typically used to assess the status of pelagic and groundfish populations. To learn more, read on or check out the Introduction vignette.

Related Projects

If you have questions or comments please contact Kelli F. Johnson.

Pinned

  1. ss3sim ss3sim Public

    An R package for stock-assessment simulation with Stock Synthesis

    R 39 23

Repositories

Showing 10 of 12 repositories
  • ss3sim Public

    An R package for stock-assessment simulation with Stock Synthesis

    R 39 23 42 1 Updated Apr 17, 2024
  • .github Public

    {ss3sim} is an R package that simplifies the steps needed to generate beautiful simulation output from the widely-used Stock Synthesis (SS3), a statistical age-structured stock assessment framework.

    0 0 0 0 Updated May 14, 2023
  • ss3models Public

    SS3 model setups for use with ss3sim

    HTML 1 0 3 0 Updated Sep 8, 2021
  • ss3sim_andersonetal Public

    Anderson et al. (2014) - a description of the ss3sim R package

    PostScript 0 0 0 0 Updated Mar 31, 2021
  • ss3sim_nin Public

    Input sample size simulations

    1 0 0 0 Updated Oct 28, 2020
  • binning Public

    Code for paper investigating the optimal way to bin composition data in stock assessments.

    R 1 0 0 0 Updated Aug 6, 2019
  • compsampling Public

    Sampling of composition data in an age-structured stock assessment model

    0 0 0 0 Updated Jul 27, 2017
  • workshop Public

    A workshop demonstration of the package

    R 0 0 2 0 Updated Jul 5, 2017
  • natural-mortality Public

    Code for Johnson et al. (2015) -- stock assessment in the face of time-varying natural mortality.

    R 0 0 0 0 Updated Apr 23, 2017
  • procdata Public

    Code to investigate interaction of process error and data weighting

    R 0 0 0 0 Updated Dec 3, 2016

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