Implements the Ridge Selection Operator (RSO)
    for variable selection in linear regression as proposed by
    Wu (2021) <doi:10.1080/00401706.2020.1791254>.
    The RSO method extends classical ridge regression by using individually
    penalized ridge parameters, inducing sparsity through reciprocal penalty parameters.
    This package provides a fast C++ implementation ('RSOFast')
    using 'Armadillo' linear algebra routines.
    The fast implementation precomputes matrix products, uses Cholesky
    factorization with primal/dual switching, and performs golden-section
    search for coordinate optimization.

Facilitates querying data from the ‘Facebook Marketing API', particularly for social science research <https://developers.facebook.com/docs/marketing-apis/>. Data from the 'Facebook Marketing API' has been used for a variety of social science applications, such as for poverty estimation (Marty and Duhaut (2024) <doi:10.1038/s41598-023-49564-6>), disease surveillance (Araujo et al. (2017) <doi:10.48550/arXiv.1705.04045>), and measuring migration (Alexander, Polimis, and Zagheni (2020) <doi:10.1007/s11113-020-09599-3>). The package facilitates querying the number of Facebook daily/monthly active users for multiple location types (e.g., from around a specific coordinate to an administrative region) and for a number of attribute types (e.g., interests, behaviors, education level, etc). The package supports making complex queries within one API call and making multiple API calls across different locations and/or parameters.

Tools for preparing inputs, running SOCSIM (SOCial SIMulator) demographic kinship microsimulations,
    and reading simulation outputs from R. The package includes helpers for
    creating simulation folders, downloading demographic rate schedules,
    starting simulations, and loading population and marriage result files.

Implements the Simulating Optimal FUNctioning framework for 
              site-scale simulations of ecosystem processes, including model 
              calibration. It contains 'Fortran 90' modules for the P-model (Stocker
              et al. (2020) <doi:10.5194/gmd-13-1545-2020>), SPLASH
              (Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>)
              and BiomeE (Weng et al. (2015)
              <doi:10.5194/bg-12-2655-2015>).