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.

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.

c(
person(given = "Eduardo", family = "García-Portugués",
role = c("aut", "cre"), email = "edgarcia@est-econ.uc3m.es",
comment = c(ORCID = "0000-0002-9224-4111")),
person(given = "Davy", family = "Paindaveine", role = "aut"),
person(given = "Thomas", family = "Verdebout", role = "aut")
)
Eduardo García-Portugués [aut, cre]
(<https://orcid.org/0000-0002-9224-4111>),
Davy Paindaveine [aut],
Thomas Verdebout [aut]

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.

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") 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.