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Dear list, here is an example of stepAIC that I do not understand. The data is n=42, Lage is the only factor and there are four other variables treated as continuous. First you see the stepAIC-forward solution (fs7). The strange thing here is that apparently not all interactions are tried for inclusion, but only WQ:Lage. In particular, I think that WFL:Lage should be tried in the last two

Dear r-helpers, I just read in an article by Virtanen et al. (2006) where vegetation-environment relationships are studied by fitting smoothed surfaces on an NMDS ordination using GAMs (Wood 2000). The authors describe, that they used R? as goodness-of-fit statistic, which they compare to the R? of fitted vectors. Calculations were carried out using the package vegan (Oksanen). I know that I can

Dear all, Does anyone knows why the results of a BIOENV (PRIMER v. 6.1.15) are diferent of the bioenv() + mantel() in vegan? Not the spearman correlation, indeed the pseudo-p value. I know that the approach bioenv() + mantel() is biased. So, how the BIOENV (PRIMER) ends with larger p values (permutated). Acctualy how the permutation test in BIOENV (PRIMER) is conducted. The user guide does not