pcnm - scaling
Hi, it is not clear for me what you mean by "is it possible to extract a spatial scale describing the spatial autocorrelation (e.g. from the eigenvalues)?". The function scores.listw is more general and returns a vector $values that are equal to Moran's I (multiplyied by a constant). Cheers,
robert.ptacnik at niva.no wrote:
Dear listers, [below message was posted on R-help already, but maybe is p?aced better here] I am using the pcnm function (spacemakeR) to obtain eigenvectors for a spatial grid of sampling sites. These pcnm eigenvectors are then used in multivariate ordination to test where community composition follows local environment or rather shows spatial autocorrelation, and get support for apatial autocorrelation. In an RDA analysis, I can see which eigenvectors correlate most with my data, which can be interpreted that the spatial scale is rather 'fine' or 'broad' (broad in case of my data). However, is there a way to read the spatial scale on which the data correlates best, i.e. is it possible to extract a spatial scale describing the spatial autocorrelation (e.g. from the eigenvalues)? My data - irregularly spaced sampling sites, total scale ca. 2000 km, most sites few tens of km apart - i use the dfunction rdist.earth to obtain a distance-matrix of all sites prior to using pcnm Thanks ! Robert
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