pcds: Proximity Catch Digraphs and Their Applications
Contains the functions for generating patterns of segregation, association, complete spatial randomness (CSR))
and Uniform data in one, two and three dimensional cases, for testing these patterns based on two invariants of
various families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2).
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>) of for two-dimensional data for visualization of PCDs for one,
two and three dimensional data. The PCD families considered are Arc-Slice PCDs,
Proportional-Edge PCDs and Central Similarity PCDs.
| Version: |
0.1.5 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
combinat, interp, gMOIP, plot3D, plotrix, Rdpack (≥ 0.7) |
| Suggests: |
knitr, scatterplot3d, spatstat.random, rmarkdown, bookdown, spelling |
| Published: |
2023-01-06 |
| Author: |
Elvan Ceyhan |
| Maintainer: |
Elvan Ceyhan <elvanceyhan at gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README |
| CRAN checks: |
pcds results |
Documentation:
Downloads:
Reverse dependencies:
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