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ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis
Simulation testing is an important approach to evaluating fishery stock assessment methods. In the last decade, the fisheries stock assessment modeling framework Stock Synthesis (SS3) has become widely used around the world. However, there lacks a generalized and scriptable framework for SS3 simulat...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974719/ https://www.ncbi.nlm.nih.gov/pubmed/24699270 http://dx.doi.org/10.1371/journal.pone.0092725 |
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author | Anderson, Sean C. Monnahan, Cole C. Johnson, Kelli F. Ono, Kotaro Valero, Juan L. |
author_facet | Anderson, Sean C. Monnahan, Cole C. Johnson, Kelli F. Ono, Kotaro Valero, Juan L. |
author_sort | Anderson, Sean C. |
collection | PubMed |
description | Simulation testing is an important approach to evaluating fishery stock assessment methods. In the last decade, the fisheries stock assessment modeling framework Stock Synthesis (SS3) has become widely used around the world. However, there lacks a generalized and scriptable framework for SS3 simulation testing. Here, we introduce ss3sim, an R package that facilitates reproducible, flexible, and rapid end-to-end simulation testing with SS3. ss3sim requires an existing SS3 model configuration along with plain-text control files describing alternative population dynamics, fishery properties, sampling scenarios, and assessment approaches. ss3sim then generates an underlying ‘truth’ from a specified operating model, samples from that truth, modifies and runs an estimation model, and synthesizes the results. The simulations can be run in parallel, reducing runtime, and the source code is free to be modified under an open-source MIT license. ss3sim is designed to explore structural differences between the underlying truth and assumptions of an estimation model, or between multiple estimation model configurations. For example, ss3sim can be used to answer questions about model misspecification, retrospective patterns, and the relative importance of different types of fisheries data. We demonstrate the software with an example, discuss how ss3sim complements other simulation software, and outline specific research questions that ss3sim could address. |
format | Online Article Text |
id | pubmed-3974719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39747192014-04-08 ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis Anderson, Sean C. Monnahan, Cole C. Johnson, Kelli F. Ono, Kotaro Valero, Juan L. PLoS One Research Article Simulation testing is an important approach to evaluating fishery stock assessment methods. In the last decade, the fisheries stock assessment modeling framework Stock Synthesis (SS3) has become widely used around the world. However, there lacks a generalized and scriptable framework for SS3 simulation testing. Here, we introduce ss3sim, an R package that facilitates reproducible, flexible, and rapid end-to-end simulation testing with SS3. ss3sim requires an existing SS3 model configuration along with plain-text control files describing alternative population dynamics, fishery properties, sampling scenarios, and assessment approaches. ss3sim then generates an underlying ‘truth’ from a specified operating model, samples from that truth, modifies and runs an estimation model, and synthesizes the results. The simulations can be run in parallel, reducing runtime, and the source code is free to be modified under an open-source MIT license. ss3sim is designed to explore structural differences between the underlying truth and assumptions of an estimation model, or between multiple estimation model configurations. For example, ss3sim can be used to answer questions about model misspecification, retrospective patterns, and the relative importance of different types of fisheries data. We demonstrate the software with an example, discuss how ss3sim complements other simulation software, and outline specific research questions that ss3sim could address. Public Library of Science 2014-04-03 /pmc/articles/PMC3974719/ /pubmed/24699270 http://dx.doi.org/10.1371/journal.pone.0092725 Text en © 2014 Anderson et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Anderson, Sean C. Monnahan, Cole C. Johnson, Kelli F. Ono, Kotaro Valero, Juan L. ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title | ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title_full | ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title_fullStr | ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title_full_unstemmed | ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title_short | ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis |
title_sort | ss3sim: an r package for fisheries stock assessment simulation with stock synthesis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974719/ https://www.ncbi.nlm.nih.gov/pubmed/24699270 http://dx.doi.org/10.1371/journal.pone.0092725 |
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