QuadratiK: Collection of Methods Constructed using Kernel-Based Quadratic
Distances
It includes test for multivariate normality, test for uniformity on the d-dimensional
Sphere, non-parametric two- and k-sample tests, random generation of points from the Poisson
kernel-based density and clustering algorithm for spherical data. For more information see
Saraceno G., Markatou M., Mukhopadhyay R. and Golzy M. (2024)
<doi:10.48550/arXiv.2402.02290>
Markatou, M. and Saraceno, G. (2024) <doi:10.48550/arXiv.2407.16374>,
Ding, Y., Markatou, M. and Saraceno, G. (2023) <doi:10.5705/ss.202022.0347>,
and Golzy, M. and Markatou, M. (2020) <doi:10.1080/10618600.2020.1740713>.
Version:
1.1.3
Depends:
R (≥ 3.5.0)
Imports:
parallel,
doParallel,
foreach,
ggplot2,
ggpubr, methods,
moments,
mvtnorm,
Rcpp,
RcppEigen,
rlecuyer,
sn, stats,
rrcov,
scatterplot3d
Suggests:
knitr,
rmarkdown,
roxygen2,
testthat (≥ 3.0.0),
rgl,
sphunif,
circular,
cluster,
clusterRepro,
mclust,
Tinflex,
movMF
Published:
2025年02月04日
Author:
Giovanni Saraceno [aut, cre] (ORCID 000-0002-1753-2367),
Marianthi Markatou [aut],
Raktim Mukhopadhyay [aut],
Mojgan Golzy [aut],
Hingee Kassel [rev],
Emi Tanaka [rev]
Maintainer:
Giovanni Saraceno <giovanni.saraceno at unipd.it>
NeedsCompilation:
yes
Language:
en-US
Documentation:
Downloads:
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