QuadratiK1.1.3 package

Collection of Methods Constructed using Kernel-Based Quadratic Distances

compare_qq

QQ-plot of given two samples using ggplot2

compute_CV

Compute the critical value for two-sample KBQD tests

compute_stats

Compute and display some descriptive statistics for the two sample tes...

cv_ksample

Compute the critical value for the KBQD k-sample tests

DOF_norm

Degrees of freedom (DOF) for the Normal kernel

DOF

Degrees of freedom (DOF) for the Poisson kernel

dpkb

The Poisson kernel-based Distribution (PKBD)

generate_SN

Generate two samples data from skew-normal distributions

kb.test-class

An S4 class for kernel-based distance tests with normal kernel

kb.test

Kernel-based quadratic distance (KBQD) Goodness-of-Fit tests

normal_CV

Compute the critical value for the KBQD tests for multivariate Normali...

pk.test-class

An S4 class for Poisson kernel-based quadratic distance tests.

pk.test

Poisson kernel-based quadratic distance test of Uniformity on the sphe...

pkbc_validation

Validation of Poisson kernel-based clustering results

pkbc-class

A S4 class for the clustering algorithm on the sphere based on Poisson...

pkbc

Poisson kernel-based clustering on the sphere

plot.pkbc

Plotting method for Poisson kernel-based clustering

poisson_CV

Compute the critical value for the Poisson KBQD tests for Uniformity

predict.pkbc

Cluster spherical observations using a mixture of Poisson kernel-based...

QuadratiK-package

Collection of Methods Constructed using the Kernel-Based Quadratic Dis...

sample_hypersphere

Generate random sample from the hypersphere

select_h

Select the value of the kernel tuning parameter

stats_clusters

Descriptive statistics for the clusters identified by the Poisson kern...

summary.kb.test

Summarizing kernel-based quadratic distance results

summary.pk.test

Summarizing kernel-based quadratic distance results

summary.pkbc

Summarizing PKBD mixture Fits

var_k

Exact variance of k-sample test

var_norm

Exact variance of normality test

var_two

Exact variance of two-sample test

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>.

  • Maintainer: Giovanni Saraceno
  • License: GPL (>= 3)
  • Last published: 2025-02-04