sphunif-package | R Documentation |
sphunif
: Uniformity Tests on the Circle, Sphere, and
HypersphereImplementation of uniformity tests on the circle and
(hyper)sphere. The main function of the package is unif_test
,
which conveniently collects more than 35 tests for assessing uniformity on
S^{p-1}=\{{\bf x}\in R^p:||{\bf x}||=1\}
, p\ge 2
. The test statistics are
implemented in the unif_stat
function, which allows computing
several statistics for different samples within a single call, thus
facilitating Monte Carlo experiments. Furthermore, the
unif_stat_MC
function allows parallelizing them in
a simple way. The asymptotic null distributions of the statistics are
available through the function unif_stat_distr
. The core of
sphunif-package
is coded in C++ by relying on the
Rcpp-package
. The package also provides several
novel datasets and gives the replicability for the data applications/
simulations in García-Portugués et al. (2021)
<doi:10.1007/978-3-030-69944-4_12>, García-Portugués et al. (2023)
<doi:10.3150/21-BEJ1454>, García-Portugués et al. (2024)
<doi:10.48550/arXiv.2108.09874>, and Fernández-de-Marcos and
García-Portugués (2024) <doi:10.48550/arXiv.405.13531>.
Eduardo García-Portugués and Thomas Verdebout.
Fernández-de-Marcos, A. and García-Portugués, E. (2024) A stereographic test of spherical uniformity. arXiv:2405.13531. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2405.13531")}.
García-Portugués, E. and Verdebout, T. (2018) An overview of uniformity tests on the hypersphere. arXiv:1804.00286. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.1804.00286")}.
García-Portugués, E., Navarro-Esteban, P., Cuesta-Albertos, J. A. (2023) On a projection-based class of uniformity tests on the hypersphere. Bernoulli, 29(1):181–204. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3150/21-BEJ1454")}.
García-Portugués, E., Navarro-Esteban, P., and Cuesta-Albertos, J. A. (2021). A Cramér–von Mises test of uniformity on the hypersphere. In Balzano, S., Porzio, G. C., Salvatore, R., Vistocco, D., and Vichi, M. (Eds.), Statistical Learning and Modeling in Data Analysis, Studies in Classification, Data Analysis and Knowledge Organization, pp. 107–116. Springer, Cham. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-3-030-69944-4_12")}.
García-Portugués, E., Paindaveine, D., and Verdebout, T. (2024). On a class of Sobolev tests for symmetry of directions, their detection thresholds, and asymptotic powers. arXiv:2108.09874v2. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2108.09874")}.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.