FLR (original) (raw)
FLR
The Fisheries Library in R, a collection of tools for quantitative fisheries science, developed in the R language, that facilitates the construction of bio-economic simulation models of fisheries systems.
Packages
The FLR toolset is composed of a series of packages offering different classes, methods and models.
FLCore
Core classes and methods for FLR.
FLa4a
The a4a population model for stock assessment and MSE.
ggplotFL
Apply ggplot2 to the FLR classes.
FLBRP
Reference Points and Fisheries Advice.
FLFleet
Modelling of fishing fleet dynamics.
FLBEIA
Bio-Economic Impact Assessment of Management strategies.
FLSAM
SAM stock assessment model in FLR.
FLXSA
Data sets and methods to simulate data.
FLAssess
Support for FLR Stock Assessment methods.
FLash
Package for fisheries forecasting.
kobe
Methods for summarising results from SAs and MSEs in the Kobe format.
FLasher
Next generation package for fisheries forecasting using Rcpp and cppAD.
FLife
Methods for incorporating life history traits and processes.
diags
Diagnostics for stock assessment methods.
mse
Tools for implementing and evaluating management procedures using MSE.
bbm
Two-stage biomass based model.
a4adiags
Perform diagnostics on a4a fit
FLSRTMB
Fit Stock-Recruitment Relationships in TMB
Installing FLR
To install the latest versions of any FLR package, and all the necessary dependencies, start R and enter
install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))
A good starting point to explore FLR is A quick introduction to FLR
About FLR
The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.
FLR development
Development code for FLR packages is available both on Github and on R-Universe. Bugs can be reported on Github as well as suggestions for further development.