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Analysing spatial point patterns in R - CSIRO

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31.3 Distance methods and summary functions 195<br />

array of G functions for amacr<strong>in</strong>e.<br />

off<br />

on<br />

fisher(Gcrossoff, off(r))<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrossoff, on(r))<br />

0.0 0.5 1.0 1.5<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrosspois(r))<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrosspois(r))<br />

on<br />

fisher(Gcrosson, off(r))<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrosson, on(r))<br />

0.0 0.5 1.0 1.5<br />

off<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrosspois(r))<br />

0.0 0.5 1.0 1.5<br />

fisher(Gcrosspois(r))<br />

As mentioned above, the function array can be <strong>in</strong>dexed by array subscripts.<br />

> data(lans<strong>in</strong>g)<br />

> a dim(a)<br />

> b aGfish data(amacr<strong>in</strong>e)<br />

> markconnect(amacr<strong>in</strong>e, "on", "off")<br />

We can use alltypes to compute the mark connection function p ij for all pairs of types i<br />

and j:<br />

> plot(alltypes(amacr<strong>in</strong>e, markconnect))<br />

Copyright<strong>CSIRO</strong> 2010

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