# [R] O-ring statistic

Rainer M Krug rkrug at sun.ac.za
Fri Dec 9 08:09:24 CET 2005

```Thanks a lot for your reply

I'll look into that and let you know if I have further questions

Rainer

> Rainer M Krug writes:
>
>  > Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004.
>  > Rings, circles and null-models for point pattern analysis in ecology.
>  > Oikos 104: 209-229 a statistic he called O-Ring statistic which is
>  > similar to Ripley's K, only that it uses rings instead of circles.
>  >
>  > http://www.oesa.ufz.de/towi/towi_programita.html#ring
>  >
>  > Is this statistic included in one of the packages in R?
>
> This kind of functionality is available in the R package `spatstat'
> (available on CRAN or from www.spatstat.org)
>
> According to the cited website, the O-ring statistic is a rescaled
> version of the pair correlation function between two types of points:
> 	O_12(r) = lambda_2 g_12(r)
>
> In spatstat, pair correlation functions are computed by the function
> 'pcf'. To estimate the cross-type pair correlation function,
> you do something like
>        pcf(Kcross(X, 1, 2))
> where X is a marked point pattern containing points of types 1 and 2.
> To estimate the intensity of type 2 points you use summary(X).
>
> Here's an example for the bivariate point pattern dataset 'amacrine'
> provided in the spatstat package. The dataset has points of two types
> labelled "on" and "off".
>
>        data(amacrine)
>        K12 <- Kcross(amacrine, "on", "off")
>        g12 <- pcf(K12, method="d", spar=0.7)
>        lambda2 <- summary(amacrine)\$marks["off","intensity"]
>        Oring <- eval.fv(lambda2 * g12)
>        plot(Oring, ylab="Oring(r)")
>
> regards
>
>

--
--
Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology (UCT)

Department of Conservation Ecology
University of Stellenbosch
Matieland 7602
South Africa

Tel:        +27 - (0)72 808 2975 (w)
Fax:        +27 - (0)21 808 3304
Cell:        +27 - (0)83 9479 042

email:    RKrug at sun.ac.za
Rainer at krugs.de

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