Package: QuadratiK 1.1.2

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>.

Authors:Giovanni Saraceno [aut, cre], Marianthi Markatou [aut], Raktim Mukhopadhyay [aut], Mojgan Golzy [aut]

QuadratiK_1.1.2.tar.gz
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QuadratiK.pdf |QuadratiK.html✨
QuadratiK/json (API)
NEWS

# Install 'QuadratiK' in R:

install.packages('QuadratiK', repos = c('https://giovsaraceno.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/giovsaraceno/quadratik-package/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

breast_cancer - Breast Cancer Wisconsin
wine - Wine data set
wireless - Wireless Indoor Localization

On CRAN:

5.90 score 1 stars 20 scripts 143 downloads 13 exports 82 dependencies

Last updated 8 days agofrom:32b794e7d0. Checks:OK: 9. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 29 2024
R-4.5-win-x86_64	OK	Oct 29 2024
R-4.5-linux-x86_64	OK	Oct 29 2024
R-4.4-win-x86_64	OK	Oct 29 2024
R-4.4-mac-x86_64	OK	Oct 29 2024
R-4.4-mac-aarch64	OK	Oct 29 2024
R-4.3-win-x86_64	OK	Oct 29 2024
R-4.3-mac-x86_64	OK	Oct 29 2024
R-4.3-mac-aarch64	OK	Oct 29 2024

Exports:dpkb kb.test pk.test pkbc pkbc_validation plot predict rpkb sample_hypersphere select_h show stats_clusters summary

Dependencies:abind backports boot broom car carData cli codetools colorspace corrplot cowplot cpp11 DEoptimR Deriv doBy doParallel dplyr fansi farver foreach Formula generics ggplot2 ggpubr ggrepel ggsci ggsignif glue gridExtra gtable isoband iterators labeling lattice lifecycle lme4 magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa mnormt modelr moments munsell mvtnorm nlme nloptr nnet numDeriv pbkrtest pcaPP pillar pkgconfig polynom purrr quantreg R6 RColorBrewer Rcpp RcppEigen rlang rlecuyer robustbase rrcov rstatix scales scatterplot3d sn SparseM stringi stringr survival tibble tidyr tidyselect utf8 vctrs viridisLite withr

Clustering algorithm on the Wireless data

Rendered fromwireless_clustering.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-09-26
Started: 2024-01-29

Introduction to the QuadratiK Package

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-10-29
Started: 2024-09-10

Random sampling from the Poisson kernel-based density

Rendered fromgenerate_rpkb.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-09-26
Started: 2024-03-28

Uniformity test on the Sphere

Rendered fromuniformity.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-09-26
Started: 2024-01-29

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Collection of Methods Constructed using the Kernel-Based Quadratic Distances	QuadratiK-package QuadratiK
Breast Cancer Wisconsin (Diagnostic)	breast_cancer
The Poisson kernel-based Distribution (PKBD)	dpkb rpkb
Kernel-based quadratic distance (KBQD) Goodness-of-Fit tests	kb.test kb.test,ANY-method show,kb.test-method
An S4 class for kernel-based distance tests with normal kernel	kb.test-class
Poisson kernel-based quadratic distance test of Uniformity on the sphere	pk.test pk.test,ANY-method show,pk.test-method
An S4 class for Poisson kernel-based quadratic distance tests.	pk.test-class
Poisson kernel-based clustering on the sphere	pkbc pkbc,ANY-method show,pkbc-method
Validation of Poisson kernel-based clustering results	pkbc_validation
A S4 class for the clustering algorithm on the sphere based on Poisson kernel-based distributions.	pkbc-class
Plotting method for Poisson kernel-based clustering	plot,pkbc,ANY-method plot.pkbc
Cluster spherical observations using a mixture of Poisson kernel-based densities	predict,pkbc-method predict.pkbc
Generate random sample from the hypersphere	sample_hypersphere
Select the value of the kernel tuning parameter	select_h
Descriptive statistics for the clusters identified by the Poisson kernel-based clustering.	stats_clusters stats_clusters,pkbc-method
Summarizing kernel-based quadratic distance results	summary,kb.test-method summary.kb.test
Summarizing kernel-based quadratic distance results	summary,pk.test-method summary.pk.test
Summarizing PKBD mixture Fits	summary,pkbc-method summary.pkbc
Wine data set	wine
Wireless Indoor Localization	wireless