Provides examples of code for analyzing data or accomplishing tasks that may be useful to institutional or educational researchers.

A comprehensive suite of tools for managing, processing, and
    analyzing data from the IFCB. I R FlowCytobot ('iRfcb') supports
    quality control, geospatial analysis, and preparation of IFCB data for
    publication in databases like <https://www.gbif.org>,
    <https://www.obis.org>, <https://emodnet.ec.europa.eu/en>,
    <https://shark.smhi.se/en/>, and <https://www.ecotaxa.org>. The package
    integrates with the MATLAB 'ifcb-analysis' tool, which is described in
    Sosik and Olson (2007) <doi:10.4319/lom.2007.5.204>, and provides
    features for working with raw, manually classified, and machine
    learning–classified image datasets. Key functionalities include image
    extraction, particle size distribution analysis, taxonomic data
    handling, and biomass concentration calculations, essential for
    plankton research.

Fits a double logistic function to NDVI time series and calculates 
             instantaneous rate of green (IRG) according to methods described
             in Bischoff et al. (2012) <doi:10.1086/667590>.

Provides the dataset and an implementation of the method illustrated in Friel, N., Rastelli, R., Wyse, J. and Raftery, A.E. (2016) <DOI:10.1073/pnas.1606295113>.

Classes and functions for metrics calculation as part of the
             'EarthScope MUSTANG' project. The functionality in this package 
             builds upon the base classes of the 'IRISSeismic' package.
             Metrics include basic statistics as well as higher level
             'health' metrics that can help identify problematic seismometers.

Provides classes and methods for seismic data analysis. The
             base classes and methods are inspired by the python code found in
             the 'ObsPy' python toolbox <https://github.com/obspy/obspy>. Additional classes and 
             methods support data returned by web services provided by the 'IRIS DMC'
             <http://service.iris.edu/>.