An R-package for fittng surplus production models in continuous-time to fisheries catch data and biomass indices (either scientific or commercial). Main advantages of spict are:
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All estimated reference points (MSY, Fmsy, Bmsy) are reported with uncertainties.
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The model can be used for short-term forecasting and management strategy evaluation.
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The model is fully stochastic in that observation error is included in catch and index observations, and process error is included in fishing and stock dynamics.
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The model is formulated in continuous-time and can therefore incorporate arbitrarily sampled data.
There is currently no manual or vignette for the package. A reasonable documentation is included in the package as help texts associated with each function (some may not be fully up-to-date). These can be accessed in the usual R manner by writing e.g. ?check.inp. A pdf compiling help texts for all functions can be downloaded here. As a new user a good start is to read ?check.inp and ?fit.spict.
The package requires TMB to be installed. TMB is now a part of CRAN and can therefore be installed using the install.packages() command. For more information about TMB click here.
To install spict from GitHub use
library(devtools)
install_github("mawp/spict/spict") # master branch
install_github("mawp/spict/spict", ref="dev") # development branch
The above procedure using install_github() should now work on Windows (make sure to remove spict before trying to reinstall). If it doesn't work the old, but tedious, procedure can be used:
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Start 64 bit R and change working directory to the (cloned or unzipped)
spictfolder. -
From R run:
source("install_windows.R")
This requires that Rtools is installed. Rtools can be obtained here. When running install_windows.R remember to set your working directory to the spict directory containing install_windows.R.