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SGCS (version 2.7)

Spatial Graph Based Clustering Summaries for Spatial Point Patterns

Description

Graph based clustering summaries for spatial point patterns. Includes Connectivity function, Cumulative connectivity function and clustering function, plus the triangle/triplet intensity function T.

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Version

Install

install.packages('SGCS')

Monthly Downloads

38

Version

2.7

License

GPL (>= 2)

Maintainer

Tuomas Rajala

Last Published

March 25th, 2019

Functions in SGCS (2.7)

default_r

Default range vector
arcs

Compute the boundary of disks
bounding_box_xy

Compute the bounding window from coordinates
clustfun

Clustering function
clustfun_denominator

Estimate the denominator of clustering function
morphoLength

Morphologicals: Relative boundary length of diluted pattern
Kfun

Ripley's K-function
translation_weights

Translation weights Compute the translation edge correction weights
pairwise_distances

pairwise distances
SGCS

SGCS: Spatial Graph based Clustering Summaries
Rfun

Clustering function versio 2
Tfun

Triplet intensity function
internalise_pp

Convert input to SGCS internal point pattern data
morphoArea

Morphologicals: Relative area fraction of diluted pattern
edge_distance

Distances to observation window edge
internal_to_ppp

Data to spatstat format
confun

Connectivity function and cumulative connectivity function.
morphoEuler

Morphologicals: Euler number of dilated pattern