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.
INSTALL

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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

Video Ync !exclusive!

The benefits of VSync include:

As the demand for video content continues to grow, platforms like VideoYNC will play a crucial role in shaping the future of video content creation and distribution. By leveraging AI, ML, and advanced analytics, VideoYNC is revolutionizing the way we create, manage, and interact with video content.

Video synchronization is the silent conductor of the production orchestra. Whether you're a YouTuber syncing a clap to a waveform, a broadcast engineer maintaining a master sync generator, or a cinematographer slating a clapperboard, you are participating in a century-old effort to make images and sound move together as one. In an era of 8K, HDR, and IP video, sync remains the absolute, non-negotiable foundation. Lose sync, and the entire illusion of moving pictures collapses into disjointed noise.

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.

Publications

Studies and publications citing or using FLR

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Community

To stay updated

You can subscribe to the FLR mailing list.

To report bugs or propose changes

Please submit an issue for the relevant package, or at the tutorials repository.