Hello, I'm trying to analyse the spatial organization of different fields planted with different varieties (each field has only one variety), but I have problems trying to understand the results of the test I did. To do this, I created different neighbourhood matrix. For example, for the first matrix, fields are considered as neighbours if they are distant from 0 to 1000 meters from each others (independently on the variety). In the second matrix, I consider fields as neighbours if they are distant from 0 to 3000 m. Then I test the spatial organization with the joincount.test function in R. The help page says "The BB join count test for spatial autocorrelation using a spatial weights matrix in weights list form for testing whether same-colour joins occur more frequently than would be expected if the zones were labelled in a spatially random way."
When I take 0 < d < 1000 m, the test gives (for variety A) : same colour statistic = 4.5, with expectation = 2.6 (highly significative). I thought this meant that one field of variety A had an average of 4.5 neighbours of the same variety A, while the expected number of neighbours of the same variety was 2.6. This means that for this variety and this range of distances, the fields are strongly organized. But, when 0 < d < 3000 m, the test gives : same colour statistic = 2.3, with expectation = 2.5. Because of this result, I'm not sure any more that the same colour statistic gives a number of neighbours of the same variety, because if it was the case, this number could have increased with increasing d, but it could not have decreased with increasing d as I found here. Can somebody help me understanding what really means this "same colour statistic"? Thanks a lot, Camille -- View this message in context: http://r.789695.n4.nabble.com/Help-joincount-test-tp4337880p4337880.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.