| title | output |
|---|---|
rcsurplus1d |
html_document |
Package rcsurplus1d lets you explore a novel surplus
production model for fisheries stock assessment. The model employs a production
function that differs from the canonical logistic (Schaefer) and Gompertz (Fox)
functions, but can still be related to the Pella-Tomlinson formulation.
In this package you can use your own data to compare the four approaches, or you can
explore the well-studied Namibian hake fishery dataset.
If you don't have the software OpenBUGS, first download and install it (http://www.openbugs.net/w/Downloads).
Then, install three packages in the following order:
devtools::install_github("rtlemos/rcrandom")
devtools::install_github("rtlemos/rcvirtual")
devtools::install_github("rtlemos/rcsurplus1d")
Load the third one:
library(rcsurplus1d)
Create your instance of the package class, and fire up the graphical user interface (GUI) on your web browser:
myinstance <- rcsurplus1d()
myinstance$gui()
To load your own data, navigate to the tab "Input"; on the left, under "Data input", you will see "Browse...". Click on it to load your CSV file, which must have the columns "year", "catch", "effort", and "cpue".
And that is it! Please read the About tabs, to understand the theoretical concepts and how to navigate the GUI. Additional information about the model can be found in Rankin and Lemos (2015).
Inside the temporary folder of your R session (tempdir()), you will find several files that may be useful for troubleshooting and running further analyses. The following short list is generated when we only run a single chain for the alternative model:
data.txt-> your fisheries dataset in a format that OpenBUGS understandsalternative_model.txt-> OpenBUGS model specificationinits1.txt-> initial values for OpenBUGS to start the model fitlog.txt-> log of model fit, including possible error messages; also includes summary statistics for model parameters and deviance information.CODAindex.txt-> key to interpretCODAchain1.txt: indicates the first and last index of each model parameter in the chainCODAchain1.txt-> vectorized MCMC array associated with the model fit