SGCS-funs {SGCS}R Documentation

Connectivity function, Cumulative Connectivity function and Clustering Function.

Description

Statistical measures based on edges of a geometric graph structure over a given point pattern data.
Date: 2009-09-08
License: GPL v2 or later

The graph structure is in this version geometric graph, meaning points x and y are connected if ||x-y||<R for the given range parameter R. Notice that in clustering function, the R equals to the parameter r.

The main function is spatial.graph.cluster.Fun, but the use of shortcuts confun, cumconfun and clustfun is highly encouraged.

In addition, the triplet intensity function T (Schladitz & Baddeley 2000) is also included for now: The Tfun.

Usage

confun(X, r=NULL, R=NULL, h=NULL, ...)
cumconfun(X, r=NULL, R=NULL, ...)
clustfun(X, r=NULL, ...)
Tfun(X, r=NULL, ...)
spatial.graph.cluster.Fun(X, r=NULL, funtype=1, funpars=0, 
                                                  minusRange=NULL, toroidal=FALSE,
                                              doDists=FALSE, doWeights=FALSE,  
                                                  prepRange=0, prepGraph=NULL, dbg=FALSE)

Arguments

X All: Point pattern object of class ppp from package spatstat.
r Vector of the range parameters in which to calculate the function value. if NULL, a range from 0 to 1/3 of window length is used.
R confun, cumconfun: Clustering radius of the graph. If NULL, R=1/sqrt(lambda).
h confun: Smoothing parameter in kernel-estimation. Box kernel width = 2h. NULL-> h=0.15*R
... Parametes for the function art1Fun:
funtype (shortcuts handle) Which function to calculate. confun=1, cumconfun=2, clustfun=3, Tfun=4.
funpars (shortcuts handle) Additional function parameter(s): confun fpar=c(R,h), cumconfun fpar=R.
minusRange clustfun, Tfun: Minus-correction parameter. Rectangular window required, NULL means no correction.
toroidal clustfun, Tfun: Toroidal correction of rectangular window.
doDists Precalculate distances for faster computation. Be aware of memory consumption n*(n-1).
doWeights confun,cumconfun: Precalculate translation correction weights for faster computation. Be aware of memory consumption O(n^2).
prepRange Preparation distance: If >0, precalculate a graph, from which it is easier to find needed connections. Useful with more complicated neighbourhoods than just the geometric (Maybe added in the future).
prepGraph An optional graph-object from spatgraphs to be used as basis for finding connections between points. Good for big datasets.
dbg Print additional messages.

Value

Object of class fv, see spatstat for details. Has plot, envelope etc. nice methods.

Author(s)

Tuomas Rajala
University of Jyvaskyla, Finland
tuomas.a.rajala@jyu.fi

References

Rajala, Penttinen: Spatial clustering and graph feature statistics (working title). Schladitz, Baddeley: A Third order point process characteristic, SJS, vol 27, 657-671, 2000.


[Package SGCS version 1.3 Index]