• Overview
•
Features
•
Installation
•
Get started
•
Long-form documentations
•
Citation
•
Contributing
•
Acknowledgments
•
References
The R package BioExtremeEvent identifies and characterises an extreme event in
time and space for a given GPS point (e.g. a sampling site) or for every pixel
in an area.
You can install the development version from GitHub with:
## Install < remotes > package (if not already installed) ----
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
## Install < BioExtremeEvent > from GitHub ----
remotes::install_github("VicoMarbec/BioExtremeEvent")Then you can attach the package BioExtremeEvent:
library("BioExtremeEvent")For an overview of the main features of BioExtremeEvent, please read
the Get
started
vignette.
BioExtremeEvent provides {{ NUMBER OF VIGNETTES }} vignettes to
learn more about the package:
- the Get started vignette describes the core features of the package
- {{ LIST ADDITIONAL VIGNETTES }}
Please cite BioExtremeEvent as:
Delannoy Victoria, Cabrol Nicolas, Fièvre Céleste, Casajus Nicolas, Villéger Sébastien*,Loiseau Nicolas* (r format(Sys.Date(), "%Y")) ioExtremeEvent: An R package to characterise extreme event. R package version 0.0.900. https://github.com/VicoMarbec/BioExtremeEvent/
All types of contributions are encouraged and valued. For more information, check out our Contributor Guidelines.
Please note that the BioExtremeEvent project is released with a
Contributor Code of
Conduct.
By contributing to this project, you agree to abide by its terms.
{{ OPTIONAL SECTION }}
The dataset used in the example comes from : Embury, O., Merchant, C.J., Good, S.A., Rayner, N.A., Høyer, J.L., Atkinson, C., Block, T., Alerskans, E., Pearson, K.J., Worsfold, M., McCarroll, N., Donlon, C., (2024). Satellite-based time-series of sea-surface temperature since 1980 for climate applications. Sci Data 11, 326. doi: https://doi.org/10.1038/s41597-024-03147-w