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Analysing spatial point patterns in R - CSIRO

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25.2 Inhomogeneous cluster models 151<br />

lty col key label<br />

bord.modif 1 1 bord.modif K[bordm](r)<br />

border 2 2 border K[bord](r)<br />

theo 3 3 theo K[pois](r)<br />

mean<strong>in</strong>g<br />

bord.modif modified border-corrected estimate of K(r)<br />

border border-corrected estimate of K(r)<br />

theo<br />

theoretical Poisson K(r)<br />

(the smooth<strong>in</strong>g parameter σ can also be controlled.)<br />

The <strong>in</strong>homogeneous analogue of the L-function is def<strong>in</strong>ed by<br />

̂L <strong>in</strong>hom (r) =<br />

√<br />

1<br />

π ̂K <strong>in</strong>hom (r)<br />

This can be computed us<strong>in</strong>g L<strong>in</strong>hom. For an <strong>in</strong>homogeneous Poisson process, L <strong>in</strong>hom (r) ≡ r.<br />

The <strong>in</strong>homogeneous analogue of the pair correlation function can be def<strong>in</strong>ed, similarly to the<br />

homogeneous case, as<br />

g <strong>in</strong>hom (r) = K′ <strong>in</strong>hom (r) .<br />

2πr<br />

It has the same <strong>in</strong>terpretation, namely, that g <strong>in</strong>hom (r) is the probability of observ<strong>in</strong>g a pair of<br />

<strong>po<strong>in</strong>t</strong>s at certa<strong>in</strong> locations separated by a distance r, divided by the correspond<strong>in</strong>g probability<br />

for a Poisson process of the same (<strong>in</strong>homogeneous) <strong>in</strong>tensity.<br />

The <strong>in</strong>homogeneous pair correlation function is computed by pcf<strong>in</strong>hom:<br />

> g g

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