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<x-charset iso-8859-1>Dear all,

I found an answer to my question (pasted below). Andersen(1992) uses an

estimator of K1,2(d) that combines the estimators K1,2 and K2,1 into a

single estimator. This estimator, mentionaed by Lotwick and Silverman

(1983), is the linear combination:

(n2K12(d) + n1K21(d))/(n1 + n2)

where n1 and n2 are the number of type 1 and type 2 events.

I hope this can help others with the same problem.

Martin Béland wrote:

*>
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*> Dear netters,
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*>
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*> I recently posted a summary of questions and responses about analyses of
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*> point patterns to study competition in mixed jack pine stands. Here is
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*> one more question that arose from running the software called
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*> "Potempkin" to compute intertype Ripley's K(d) analysis :
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*>
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*> I thought that bivariate analysis of interaction between species 1 and 2
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*> should be the same as that of interaction between species 2 and 1. The
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*> output given by potemkin for the bivariate analysis includes K1,1 K1,2
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*> K2,1 and K2,2. The values for K1,2 and K2,1 for short values of d are
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*> the same but as d increases, K2,1 becomes larger that K1,2. The
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*> confidance intervals are different from the beginning. How do you
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*> explain this?
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*>
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*> To this, John Brzustowski, the author of the programm replied to me
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*>
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*> > Good question. I don't seem to have a paper describing the bivariate
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*> > K here, but what I think is happening is this:
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*> > The obvious definition for bivariate K(t) would be the proportion of
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*> > pairs of individuals, the first of species 1, the second of species 2,
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*> > that lie within a distance t or less of each other. That would give a
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*> > symmetric definition. But I think Ripley does this a bit differently:
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*> > K1,2 (t) is the average, over all individuals in species 1, of the
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*> > proportion of species 2 neighbours that are within distance t of the
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*> > individual in species 1. This is a bit tricky, but it just amounts to
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*> > weighting the pairs differently in each case. I suppose an advantage
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*> > of this approach is it should allow one to detect attraction of
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*> > species 1 by species 2, as opposed to the other way around. Maybe.
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*> >
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*>
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*> Does any of you know:
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*> 1- if other software compute the bivariate K(t) in a different way that
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*> use a symmetric definition of the interaction? and
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*> 2- if there is no other way to compute the bivariate K(t), how do you
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*> suggest the result must be interpreted, that is, which of K1,2 or K2,1
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*> must be used in which situation?
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*>
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*> Any help would be appreciated,
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*>
*

Martin Béland, biologiste, Ph.D. Env.

Unité de recherche et de développement forestiers de

l'Abitibi-Témiscamingue

Université du Québec en Abitibi-Témiscamingue

445, boulevard Université

Rouyn-Noranda (Québec) J9X 5E4

Téléphone : (819) 762-0971 #2458

Fax : (819) 797-4727

Courriel : martin.beland@uqat.uquebec.ca

</x-charset>

**Next message:**Antoine Guisan: "offres PhD en Suisse"**Previous message:**Goreaud Francois: "Suite de la reponse a Olivier, concernant une utilisation du modu le Ripley sur ADS"**In reply to:**Martin Béland: "Re: Potemkin"**Next in thread:**Goreaud Francois: "RE: Bivariate Ripley's K"**Maybe reply:**Goreaud Francois: "RE: Bivariate Ripley's K"**Reply:**Raphael Pelissier: "Re: Bivariate Ripley's K"**Messages sorted by:**[ date ] [ thread ] [ subject ] [ author ]

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