The Metapopulation Assessment System (MAS) is a modular tool for creating and fitting fisheries stock assessment models. The R interface to MAS (r4MAS) allows users to build and run MAS models directly using the
R language. It also includes functions to help translate between MAS and other stock assessment software and to plot outputs of MAS models, including estimates of key biological and observation parameters and derived quantities such as biological reference points, estimated biomass, and estimated numbers-at-age.
This tool is supported by the NOAA Fisheries Integrated Toolbox. More information can be found on the toolbox landing page
Since this package contains C++ files, you will need to ensure you have a C++ compiler installed. You can install a C++ compiler here, please make sure it is C++14 or more recent.
You will also need to have the
Rcpp package installed.
Please install and load
r4MAS from Github using the
remotes package as follows:
Windows users: Please ensure you have Rtools. If you receive errors related to C++ when loading r4MAS, it could be because your R installation uses the default Makevars.win file. To update your Makevars.win file, please run the following code in your R terminal:
dotR <- file.path(Sys.getenv("HOME"), ".R") if (!file.exists(dotR)) dir.create(dotR) M <- file.path(dotR, "Makevars.win") if (!file.exists(M)) file.create(M) cat("\nCXX14FLAGS=-O3 -Wno-unused-variable -Wno-unused-function", "CXX14 = $(BINPREF)g++ -m$(WIN) -std=c++1y", "CXX11FLAGS=-O3 -Wno-unused-variable -Wno-unused-function", file = M, sep = "\n", append = TRUE)
To get notifications about
r4MAS, you can watch this GitHub project.
Once you’ve installed the package and have confirmed you can load it, we recommend starting with the introductory vignette to see an example of building and running a simple model within r4MAS. The write_test_data() function will generate simple dummy input data. You can replace these dummy data with your own data.
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