Programmatic interface to several NASA Earth Observation 'OPeNDAP' servers (Open-source Project for a Network Data Access Protocol) (<https://www.opendap.org/>). Allows for easy downloads of MODIS subsets, as well as other Earth Observation datacubes, in a time-saving and efficient way : by sampling it at the very downloading phase (spatially, temporally and dimensionally).

Programmatic interface to the Oak Ridge National Laboratories
    'MODIS Land Products Subsets' web services 
    (<https://modis.ornl.gov/data/modis_webservice.html>). Allows for easy
    downloads of 'MODIS' time series directly to your R workspace or
    your computer.

Provides a robust implementation of information-theoretic moderation analysis
    using multi-model inference based on Akaike's Information Criterion (AIC) and its small-sample corrected form (Corrected AIC).
    The package enables researchers to compare competing model specifications
    and helps distinguish true interaction effects from nonlinear relationships
    that may produce spurious moderation. The methods build on Daryanto (2019)
    <doi:10.1016/j.jbusres.2019.06.012>.

Calculate predicted levels and marginal effects,
    using the delta method to calculate standard errors. This is an R-based
    version of the 'margins' command from Stata.

The algorithms implemented here are used to detect the community structure of a network. 
            These algorithms follow different approaches, but are all based on the concept of modularity maximization.

Methods for modeling moderator variables in cross-sectional, temporal, and multi-level networks. Includes model selection techniques and a variety of plotting functions. Implements the methods described by Swanson (2020) <https://www.proquest.com/openview/d151ab6b93ad47e3f0d5e59d7b6fd3d3>.

'MatLab'-Style Modeling of Optimization Problems with 'R'. This package provides a set of convenience functions to transform a 'MatLab'-style optimization modeling structure to its 'ROI' equivalent.