pcds: Proximity Catch Digraphs and Their Applications

Contains the functions for construction and visualization of various families of the proximity catch digraphs (PCDs), see (Ceyhan (2005) ISBN:978-3-639-19063-2), for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) or uniformity in one, two and three dimensional cases. The package also has tools for generating points from these spatial patterns. The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi:10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs, and Central Similarity PCDs.

Version:	0.1.8
Depends:	R (≥ 3.5.0)
Imports:	combinat, interp, gMOIP, plot3D, plotrix, Rdpack (≥ 0.7)
Suggests:	knitr, scatterplot3d, spatstat.random, rmarkdown, bookdown, spelling
Published:	2023-12-19
Author:	Elvan Ceyhan [aut, cre]
Maintainer:	Elvan Ceyhan <elvanceyhan at gmail.com>
License:	GPL-2
NeedsCompilation:	no
Language:	en-US
Materials:	README
CRAN checks:	pcds results

Documentation:

Reference manual:	pcds.pdf
Vignettes:	VS0 - Introduction to pcds VS1.1 - Example: An Artificial 2D Dataset VS1.2 - A Real-Life Example: Swamp Tree Data VS1.3 - Example: An Artificial 1D Dataset VS2.1 - Illustration of PCDs in One Triangle VS2.2 - Illustration of PCDs in One Interval VS2.3 - Illustration of PCDs in One Tetrahedron VS3 - Spatial Point Patterns VS4 - Extrema in Delaunay Cells VS5 - Functions for Euclidean Geometry

Downloads:

Package source:	pcds_0.1.8.tar.gz
Windows binaries:	r-devel: pcds_0.1.8.zip, r-release: pcds_0.1.8.zip, r-oldrel: pcds_0.1.8.zip
macOS binaries:	r-release (arm64): pcds_0.1.8.tgz, r-oldrel (arm64): pcds_0.1.8.tgz, r-release (x86_64): pcds_0.1.8.tgz, r-oldrel (x86_64): pcds_0.1.8.tgz
Old sources:	pcds archive

Reverse dependencies:

Reverse imports:

nnspat, pcds.ugraph

Linking:

Please use the canonical form https://CRAN.R-project.org/package=pcds to link to this page.