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Life and Fishery","monthly_downloads":664,"total_dependent_repos":2,"total_dependent_packages":0,"readme":"# ss3sim\n\nss3sim is an R package that simplifies the steps needed to generate beautiful\nsimulation output from the widely-used [Stock\nSynthesis](https://nmfs-ost.github.io/ss3-doc/) (SS3) assessment framework. To\nlearn more, read on or check out the [Introduction\nvignette](https://ss3sim.github.io/ss3sim/articles/introduction.html) on the\n[ss3sim website](https://ss3sim.github.io/ss3sim/).\n\n## Table of contents\n\n- [ss3sim](#ss3sim)\n  - [Table of contents](#table-of-contents)\n  - [Installation](#installation)\n  - [Simulation setup](#simulation-setup)\n  - [How ss3sim works](#how-ss3sim-works)\n    - [Example output from a simulation](#example-output-from-a-simulation)\n  - [Citing ss3sim](#citing-ss3sim)\n  - [Contributing to ss3sim](#contributing-to-ss3sim)\n    - [Code of conduct](#code-of-conduct)\n    - [Disclaimer](#disclaimer)\n\n## Installation\n\nBelow are instructions for installing ss3sim from GitHub, which is the\npreferred approach. Users can use\n[remotes](https://github.com/r-lib/remotes),\n[devtools](https://github.com/r-lib/devtools), or\n[pak](https://github.com/r-lib/pak)\nto do this, though the example below is for the latter. `\"main\"` is the default\nbranch with the latest code, all developmental features will be in feature\nbranches.\n\nInstall the GitHub version via {pak}:\n\n``` r\n# install.packages(\"pak\")\npak::pkg_install(\"ss3sim/ss3sim\")\n```\n\nThe [CRAN version](https://cran.r-project.org/package=ss3sim) of ss3sim is not\nregularly updated, and thus, it is not recommended to install from CRAN. We\nsuggest using the GitHub version because it comes with the SS3\nexecutable/binary. If you are using the CRAN version, you will need to install\nthe binary and place it in your system path. See the [SS3 Release\npage](https://github.com/nmfs-ost/ss3-source-code/releases) for an executable\nthat will work on your operating system and the SS3 documentation for [how to\nplace the executable in your\npath](https://nmfs-ost.github.io/ss3-doc/SS330_User_Manual_release.html#putting-stock-synthesis-in-your-path).\n\nOnce ss3sim is installed, you can read the help files and access the\n[Introduction\nvignette](https://ss3sim.github.io/ss3sim/articles/introduction.html)\nfor reproducible examples of ss3sim. See below for code how to do both.\n\n``` r\n?ss3sim\nbrowseVignettes(\"ss3sim\")\nvignette(\"introduction\", \"ss3sim\")\n```\n\n## Simulation setup\n\nAn ss3sim simulation requires three types of input:\n\n1. a base model of the underlying truth (an SS3 operating model; OM),\n1. an SS3 estimation method (EM) to assess the current status, and\n1. a data frame specifying how you want to manipulate (1) and (2) from their\n   status-quo configurations.\n\nYou can find [examples of an OM and EM on\nGitHub](https://github.com/ss3sim/ss3sim/tree/master/inst/extdata/models) or\nlocally on your machine if you have installed ss3sim. To find the location of\nthese files locally, run `system.file(\"extdata\", \"models\", package =\n\"ss3sim\")`. Users often modify these files to create new life histories or\nmodify their own files from a production stock assessment to work within\nss3sim. See the vignettes [on modifying\nmodels](https://ss3sim.github.io/ss3sim/articles/modifying-models.html) and\n[making models](https://ss3sim.github.io/ss3sim/articles/making-models.html)\nfor more information.\n\nAn example data frame for (3) is also available within the package via\n`ss3sim::setup_scenarios_defaults()`. This example is sufficient to run a\nsingle scenario using the OM and EM supplied in the package. Many more options\n(i.e., columns) are possible and users should take note that this example\nprovided in the package represents a minimum viable setup. Users can either\ncreate their own data frame in R or augment this existing data frame to run a\nset of custom scenarios. Specifically, adding columns will enable the\nmanipulation of additional components of the OM, sampling procedure, or the EM.\nAdding rows will lead to more scenarios, where a scenario is the result of the\ncombination of specifications in that row, i.e., how you manipulate the OM and\nthe EM.\n\nss3sim stores each scenario in its own directory. Inside the scenario directory\nwill be one directory per iteration. Iterations within a scenario differ only\nby the seed used within R to define the randomness of that iteration. See the\nfigure below for an example directory structure from a simulation with two\nscenarios and 3 iterations.\n\n``` text\n├📁 scenario 1\n│   ├📁  1\n│   │    ├📁  OM\n│   │    └📁  EM\n│   ├📁  2\n│   │    ├📁  OM\n│   │    └📁  EM\n│   └📁  3\n│        ├📁  OM\n│        └📁  EM\n└📁 scenario 2\n    ├📁  1\n    │     ├📁  OM\n    │     └📁  EM\n    ├📁  2\n    │     ├📁  OM\n    │     └📁  EM\n    └📁  3\n         ├📁  OM\n         └📁  EM\n```\n\n## How ss3sim works\n\nss3sim works by converting information stored in the columns of your data frame\nthat stores your simulation specifications (e.g., `example_df_configuration`)\ninto function arguments. Functions within the ss3sim package use these\narguments to manipulate the associated OM and EM files such that the\nappropriate simulated data is generated and used to fit the EM. For example,\nthe first row of the simulation argument for the observation error of the index\nmight be equal to 0.4 if you want a noisy survey\n\n``` r\nexample_df_configuration \u003c- ss3sim::setup_scenarios_defaults()\nexample_df_configuration[1, \"si.sds_obs.2\"] \u003c- 0.4\n```\n\nss3sim functions are divided into the following three types of functions:\n\n1. `change` and `sample` functions that manipulate SS3 configuration files.\n   These manipulations generate the underlying \"truth\" (OMs) and control the\n   assessment of the truth (EMs).\n2. `run` functions that conduct simulations. These functions generate a folder\n   structure, call manipulation functions, run SS3 as needed, and save the\n   output.\n3. `get` functions that synthesize the output.\n\n### Example output from a simulation\n\n```r\ndata(\"scalar_dat\", package = \"ss3sim\")\np \u003c- scalar_dat |\u003e\n  dplyr::mutate(\n    M = ifelse(NatM_p_1_Fem_GP_1 == 0.2, \"M = 0.2\", \"M = Estimated\")\n  ) |\u003e\n  dplyr::filter(model_run == \"em\") |\u003e\n  ggplot2::ggplot(ggplot2::aes(x = LnQ_base_Survey_2, y = depletion)) +\n  ggplot2::geom_point() +\n  ggplot2::facet_grid(\"M\") +\n  ggplot2::xlab(\"Survey scalar (q)\") +\n  ggplot2::ylab(\"Depletion\")\nprint(p)\n```\n\nYou can run the code below to visualize the results of a simulation with two\nscenarios, one that fixed natural mortality (*M*) at its true value from the OM\n(*M* = 0.2) and one that estimated *M*. The upper panel shows how the estimates\ndepletion change as the estimate of *q* changes for when *M* is fixed at the\ntruth and the lower panel shows the same relationship when *M* is estimated.\n\n## Citing ss3sim\n\nIf you use ss3sim in a publication, please cite it as shown by\n\n``` r\ncitation(\"ss3sim\")\ntoBibtex(citation(\"ss3sim\"))\n```\n\n## Contributing to ss3sim\n\nInterested in contributing to ss3sim? We recognize and appreciate that\ncontributions come in many forms, including but not limited to writing code,\nreporting issues, and creating examples and/or documentation.\n\nWe strive to follow the [NMFS Fisheries Toolbox Contribution\nGuide](https://github.com/nmfs-fish-tools/Resources/blob/main/CONTRIBUTING.md).\nWe also have included ss3sim-specific code contribution information in the\n[Developers page of the ss3sim\nwiki](https://github.com/ss3sim/ss3sim/wiki/developers). Note that these are\nguidelines, not rules, and we are open to collaborations in other ways that may\nwork better for you. Please feel free to reach out to us by opening an issue in\nthis repository or by emailing the maintainer (run `maintainer(\"ss3sim\")` in R\nto view the current maintainer's name and email address).\n\nNote that contributors are expected to uphold the [code of conduct](#code-of-conduct).\n\n### Code of conduct\n\nThis project and everyone participating in it is governed by the [NMFS\nFisheries Toolbox Code of\nConduct](https://github.com/nmfs-fish-tools/Resources/blob/main/CODE_OF_CONDUCT.md).\nBy participating, you are expected to uphold this code. Please report\nunacceptable behavior to\n[fisheries.toolbox@noaa.gov](mailto:fisheries.toolbox@noaa.gov). Note that the\nmaintainers of ss3sim do not have access to this email account, so unacceptable\nbehavior of maintainers can also be reported here.\n\n### Disclaimer\n\n\"The United States Department of Commerce (DOC) GitHub project code is provided\non an 'as is' basis and the user assumes responsibility for its use. DOC has\nrelinquished control of the information and no longer has responsibility to\nprotect the integrity, confidentiality, or availability of the information. Any\nclaims against the Department of Commerce stemming from the use of its GitHub\nproject will be governed by all applicable Federal law. Any reference to\nspecific commercial products, processes, or services by service mark,\ntrademark, manufacturer, or otherwise, does not constitute or imply their\nendorsement, recommendation or favoring by the Department of Commerce. The\nDepartment of Commerce seal and logo, or the seal and logo of a DOC bureau,\nshall not be used in any manner to imply endorsement of any commercial product\nor activity by DOC or the United States Government.\"\n\n[U.S. Department of Commerce](https://www.commerce.gov/) | [National\nOceanographic and Atmospheric Administration](https://www.noaa.gov) | [NOAA\nFisheries](https://www.fisheries.noaa.gov/)\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["fisheries-stock-assessment","noaa-nsap","stock-assessment","latex"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/1078","html_url":"https://ost.ecosyste.ms/projects/1078"}