[adegenet-forum] sPCA: Calculation of spatial autocorrelation for PA data

[Jombart, Thibaut]

Hello, 

Moran's I is computed for binary data as for continuous characters. While developed for continuous traits originally, the index makes perfect sense for binary data. The lag vector is the mean presence over neighbouring sites, and Moran's index is a dot product between presence at sites and these lagged values (divided by the variance).

Cheers
Thibaut


________________________________________
From: adegenet-forum-bounces at lists.r-forge.r-project.org [adegenet-forum-bounces at lists.r-forge.r-project.org] on behalf of Vanesse Labeyrie [vanesse.labeyrie at cirad.fr]
Sent: 15 April 2013 12:53
To: adegenet-forum at lists.r-forge.r-project.org
Subject: [adegenet-forum] sPCA: Calculation of spatial autocorrelation for      PA data

  Hi,

I did not found details concerning the calculation of the spatial
autocorrelation index for presences/absence ("PA") data in the sPCA.

I want to use sPCA for a species inventory table (presence of the
species coded 1 and absence 0), and I would like to know how the spatial
autocorrelation is calculated for this kind of data, as I thought
Moran's I is used for continuous numerical data only.

Many thanks for you answer

--
Vanesse LABEYRIE

CIRAD Montpellier

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