MATSS is a package for conducting Macroecological Analyses of Time Series Structure. We designed it to help researchers quickly get started in analyses of ecological time series, and to reinforce and spread good practices in computational analyses.
We provide functionality to:
For more information about contributing code, datasets, or analyses, please check out the Contributing Guide.
You can install
MATSS from github with:
# install.packages("remotes") remotes::install_github("weecology/MATSS", build_opts = c("--no-resave-data", "--no-manual"))
MATSS also uses the
rdataretriever package to download additional datasets. To get this package and its dependencies wokring, we recommend following the online installation instructions.
MATSS pulls data from a variety of sources, including:
Combined, there are 320483 individual time series across all of these data sources.
We recommend you take a look at our vignette on Getting Started for more details about how to begin using
If you have the package installed, you can also view the vignette from within R:
Here are some examples of analyses built on
We thank Erica Christensen and Joan Meiners for their contributions and input on early prototypes of this project. This project would not be possible without the support of Henry Senyondo and the retriever team. Finally, we thank Will Landau and the drake team for their input and responsiveness to feedback.
Package development is supported through various funding sources: including the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative, Grant GBMF4563 to E. P. White (supporting also the time of J. Simonis and H. Ye), the National Science Foundation, Grant DEB-1622425 to S. K. M. Ernest, and a National Science Foundation Graduate Research Fellowship (No. DGE-1315138 and DGE-1842473) to R. Diaz.