num.delaunay.tri

Returns the number of Delaunay triangles
based on the 2D set of points <code>Yp</code>.
See (okabe:2000,sinclair:2016;textualpcds)
for more on Delaunay triangulation and
the corresponding algorithm.

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.

Elvan Ceyhan

pcds

Proximity Catch Digraphs and Their Applications

num.delaunay.tri function

<dl><dt>Yp</dt>
<dd>A set of 2D points
which constitute the vertices of Delaunay triangles.</dd></dl>

Arguments

Author

Number of Delaunay triangles based on a 2D data set — num.delaunay.tri

<dl>

<dt>Yp</dt>
<dd>A set of 2D points
which constitute the vertices of Delaunay triangles.</dd>

</dl>

num.delaunay.tri: Number of Delaunay triangles based on a 2D data set

Description

Usage

Value

Arguments

Author

References

See Also

Examples