This function lists every component used by the CMSY++ functions of the package, with its
version, download link, file size, checksums (MD5 and SHA-256), licence and the reference to
cite: the CMSY++ code, neural network, user guide and training data (bundled with the
package), the JAGS installers for each operating system, the rjags package, the other R
packages CMSY++ uses, and the FishBase and SeaLifeBase releases behind the built-in table of
priors (see cmsy_priors()).
Details
The CMSY++ files bundled with the package are the unmodified March 2021 release from GEOMAR's
repository OceanRep (record 52147), published under the CC BY 4.0 licence; the same code is on
GitHub at https://github.com/SISTA16/cmsyPlusPlus. cmsy_run() applies a few documented
changes to a copy of the code before running it (see cmsy_system()); they do not change the
method. faofishingreport is not affiliated with or endorsed by the authors of CMSY++.
References
Froese, R., Winker, H., Coro, G., Palomares, M.L.D., Tsikliras, A.C., Dimarchopoulou, D., Touloumis, K., Demirel, N., Vianna, G.M.S., Scarcella, G., Schijns, R., Liang, C. and Pauly, D. (2023). New developments in the analysis of catch time series as the basis for fish stock assessments: the CMSY++ method. Acta Ichthyologica et Piscatoria 53: 173-189. doi:10.3897/aiep.53.105910
Froese, R., Demirel, N., Coro, G. and Winker, H. (2021). User Guide for CMSY++. GEOMAR, Germany, 17 pp. https://oceanrep.geomar.de/id/eprint/52147/
Plummer, M. (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), Vienna. https://mcmc-jags.sourceforge.io/
Examples
# Every component, with version, file, licence and link
src <- cmsy_sources()
src[, c("component", "version", "platform", "file", "license")]
#> component version platform
#> 1 CMSY++ code 16 (January 2021) all
#> 2 CMSY++ neural network 16 (January 2021) all
#> 3 CMSY++ user guide March 2021 all
#> 4 CMSY++ training data (catch) 9e all
#> 5 CMSY++ training data (stocks) 9e all
#> 6 JAGS 4.3.2 windows
#> 7 JAGS 4.3.1 windows
#> 8 JAGS 4.3.2 macos
#> 9 JAGS 4.3.1 macos
#> 10 JAGS 4.3.2 source
#> 11 JAGS 5.0.0 windows
#> 12 JAGS 5.0.0 macos
#> 13 JAGS 5.0.0 source
#> 14 rjags 4-17 all
#> 15 rjags 5-3 windows
#> 16 rjags 5-3 macos-arm64
#> 17 rjags 5-3 macos-x86_64
#> 18 rjags 5-3 source
#> 19 snpar (runs test reproduced in cmsy_run()) 1.0 all
#> 20 R2jags 0.8-9 all
#> 21 coda 0.19-4.1 all
#> 22 gplots 3.3.0 all
#> 23 mvtnorm 1.4-2 all
#> 24 neuralnet 1.44.2 all
#> 25 conicfit 1.0.4 all
#> 26 FishBase 26.06 all
#> 27 SeaLifeBase 26.06 all
#> file
#> 1 CMSY++16.R
#> 2 ffnn.bin
#> 3 CMSYUserGuideMarch2021.pdf
#> 4 Train_Catch_9e.csv
#> 5 Train_ID_9e.csv
#> 6 JAGS-4.3.2.exe
#> 7 JAGS-4.3.1.exe
#> 8 JAGS-4.3.2.pkg
#> 9 JAGS-4.3.1.pkg
#> 10 JAGS-4.3.2.tar.gz
#> 11 JAGS-5.0.0.exe
#> 12 JAGS-5.0.0-universal.pkg
#> 13 JAGS-5.0.0.tar.gz
#> 14 rjags
#> 15 rjags_5-3.zip
#> 16 rjags_5-3-R4.6.1-arm64.tgz
#> 17 rjags_5-3-R4.6.1-x86_64.tgz
#> 18 rjags_5-3.tar.gz
#> 19 snpar_1.0.tar.gz
#> 20 R2jags
#> 21 coda
#> 22 gplots
#> 23 mvtnorm
#> 24 neuralnet
#> 25 conicfit
#> 26 species, synonyms, stocks, estimate
#> 27 species, synonyms, stocks, estimate
#> license
#> 1 CC BY 4.0
#> 2 CC BY 4.0
#> 3 CC BY 4.0
#> 4 CC BY 4.0
#> 5 CC BY 4.0
#> 6 GPL-2
#> 7 GPL-2
#> 8 GPL-2
#> 9 GPL-2
#> 10 GPL-2
#> 11 GPL-2
#> 12 GPL-2
#> 13 GPL-2
#> 14 GPL-2
#> 15 GPL-2
#> 16 GPL-2
#> 17 GPL-2
#> 18 GPL-2
#> 19 GPL (>= 2)
#> 20 GPL (> 2)
#> 21 GPL (>= 2)
#> 22 GPL-2
#> 23 GPL-2
#> 24 GPL (>= 2)
#> 25 GPL (>= 3)
#> 26 CC BY-NC 4.0 (FishBase.org team, as stated for the snapshots)
#> 27 CC BY-NC 4.0 (FishBase.org team, as stated for the snapshots)
# The JAGS installers for each system, with their checksums
cmsy_sources("JAGS")[, c("component", "version", "platform", "url", "sha256")]
#> component version platform
#> 1 JAGS 4.3.2 windows
#> 2 JAGS 4.3.1 windows
#> 3 JAGS 4.3.2 macos
#> 4 JAGS 4.3.1 macos
#> 5 JAGS 4.3.2 source
#> 6 JAGS 5.0.0 windows
#> 7 JAGS 5.0.0 macos
#> 8 JAGS 5.0.0 source
#> 9 rjags 4-17 all
#> 10 rjags 5-3 windows
#> 11 rjags 5-3 macos-arm64
#> 12 rjags 5-3 macos-x86_64
#> 13 rjags 5-3 source
#> 14 R2jags 0.8-9 all
#> url
#> 1 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Windows/JAGS-4.3.2.exe
#> 2 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Windows/JAGS-4.3.1.exe
#> 3 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Mac%20OS%20X/JAGS-4.3.2.pkg
#> 4 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Mac%20OS%20X/JAGS-4.3.1.pkg
#> 5 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Source/JAGS-4.3.2.tar.gz
#> 6 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/5.x/Windows/Rtools45/JAGS-5.0.0.exe
#> 7 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/5.x/macOS/JAGS-5.0.0-universal.pkg
#> 8 https://downloads.sourceforge.net/project/mcmc-jags/JAGS/5.x/Source/JAGS-5.0.0.tar.gz
#> 9 https://cran.r-project.org/package=rjags
#> 10 https://downloads.sourceforge.net/project/mcmc-jags/rjags/5/Windows/Rtools45/rjags_5-3.zip
#> 11 https://downloads.sourceforge.net/project/mcmc-jags/rjags/5/macOS/rjags_5-3-R4.6.1-arm64.tgz
#> 12 https://downloads.sourceforge.net/project/mcmc-jags/rjags/5/macOS/rjags_5-3-R4.6.1-x86_64.tgz
#> 13 https://downloads.sourceforge.net/project/mcmc-jags/rjags/5/Source/rjags_5-3.tar.gz
#> 14 https://cran.r-project.org/package=R2jags
#> sha256
#> 1 197f3b32f35462fdbbb566035f459bade6c61207fb2bada265be1504c0fa414f
#> 2 e7f1ea777749b17c0d64f07d80f9c3a93a5f95fa6b0b009f1568858b0106a2b3
#> 3 14d171621a582d29a7e6ce11eccf853170367c17d41554e07b88abed76a2fb7e
#> 4 6f8f220f975556aec82275c93a4556184476f4d32ee828ee8f839590fe7c94bb
#> 5 871f556af403a7c2ce6a0f02f15cf85a572763e093d26658ebac55c4ab472fc8
#> 6 f79f4af3da180f9e9a7c1c1ff036e806063d883ee485b5e7a458c50b0315acd4
#> 7 49753af665f4ebe309c4b1b7b7d53fd10009b5b19ed766e040e5581842772316
#> 8 64fcd4883b8a8ee907722f49366cc9f277477a0647ada61356f17568f84ffff8
#> 9 <NA>
#> 10 2e063131bd7200de18268d7579c7f927d22b2745c178b809b160e9213970abee
#> 11 1fe67195947f9cb0df085b8d434e348a6bf4c69108bf4fa78ceee0cc5d322d5c
#> 12 c39a3527e2580271113c76c4ea504b6553d2eed7f17dd271c8ff966223b82d72
#> 13 dac0e7f2da817a15d8a796025ce2f36f0aa3154921bd520be4f98df2753f617a
#> 14 <NA>
# The references to cite
unique(src$citation[nzchar(src$citation)])
#> [1] "Froese R, Winker H, Coro G, Palomares MLD, Tsikliras AC, Dimarchopoulou D, Touloumis K, Demirel N, Vianna GMS, Scarcella G, Schijns R, Liang C, Pauly D (2023). New developments in the analysis of catch time series as the basis for fish stock assessments: the CMSY++ method. Acta Ichthyologica et Piscatoria 53: 173-189. https://doi.org/10.3897/aiep.53.105910"
#> [2] "Froese R, Demirel N, Coro G, Winker H (2021). User Guide for CMSY++. GEOMAR, Germany, 17 pp. https://oceanrep.geomar.de/id/eprint/52147/"
#> [3] "Plummer M (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of DSC 2003, Vienna. https://mcmc-jags.sourceforge.io/"
#> [4] "citation(\"rjags\")"
#> [5] "Qiu D (2014). snpar: Supplementary Non-parametric Statistics Methods. R package version 1.0."
#> [6] "citation(\"R2jags\")"
#> [7] "citation(\"coda\")"
#> [8] "citation(\"gplots\")"
#> [9] "citation(\"mvtnorm\")"
#> [10] "citation(\"neuralnet\")"
#> [11] "citation(\"conicfit\")"
#> [12] "Froese R, Pauly D (Eds.) (2026). FishBase. World Wide Web electronic publication, version (06/2026). https://www.fishbase.se"
#> [13] "Palomares MLD, Pauly D (Eds.) (2026). SeaLifeBase. World Wide Web electronic publication, version (06/2026). https://www.sealifebase.se"