ROSE (RObust Semiparametric Efficient) random forests for robust 
  semiparametric efficient estimation in partially parametric models (containing 
  generalised partially linear models).
  Details can be found in the paper by Young and Shah (2024) <doi:10.48550/arXiv.2410.03471>.

Download and plot Open Street Map <https://www.openstreetmap.org/>,
    Bing Maps <https://www.bing.com/maps> and other tiled map sources. Use to create 
    basemaps quickly and add hillshade to vector-based maps.

Allows one to use 'Osmium Tool'
    (<https://osmcode.org/osmium-tool/>) from R. 'Osmium' is a
    multipurpose command line tool that enables one to manipulate and
    analyze OpenStreetMap files through several different commands.
    Currently, this package does not aim to offer functions that cover the
    entire 'Osmium' API, instead making available functions that wrap only
    a very limited set of its features.

Implementation of robust sparse PCA using the ROSPCA algorithm 
             of Hubert et al. (2016) <DOI:10.1080/00401706.2015.1093962>.

Connect, query, and operate on information available from the 
    'Open Source Vulnerability' database <https://osv.dev/>. Although 'CRAN' 
    has vulnerabilities listed, these are few compared to projects such as 
    'PyPI'. With tighter integration between 'R' and 'Python', having an 
    'R' specific package to access details about vulnerabilities from 
    various sources is a worthwhile enterprise.

Implementation of the tests for rotational symmetry on the
    hypersphere proposed in García-Portugués, Paindaveine and Verdebout (2020)
    <doi:10.1080/01621459.2019.1665527>. The package also implements the
    proposed distributions on the hypersphere, based on the tangent-normal
    decomposition, and allows for the replication of the data application
    considered in the paper.

Fit and deploy rotation forest models ("Rodriguez, J.J., Kuncheva,
    L.I., 2006. Rotation forest: A new classifier ensemble method. IEEE Trans.
    Pattern Anal. Mach. Intell. 28, 1619-1630 <doi:10.1109/TPAMI.2006.211>") for binary classification.
    Rotation forest is an ensemble method where each base classifier (tree) is
    fit on the principal components of the variables of random partitions of
    the feature set.