Dear R members,
I understand the main principles why R-Vegan does not provide p-values for the
biplot scores and/or canonical coefficients (see also post on stackoverflow).
(i) We can obtain linear regression statistics and refit an ordination result
as multiple response linear model (lm, see as.mlm.cca). This regression ignores
residual unconstrained variation in the data. However, constrained ordination
is based on iteration with regression. My question is now, how does ordination
considers this unconstrained variation? By the unimodal distribution of the
data (cca). By the selected distance matrix (Chi, Euclidian)? Or is the
difference based on the fact, that ordination is a multivariate analyses?
(ii) I think question (i) is the reason why I get difference between biplot
scores (integral of rda) and scores() (equivalent of regression coefficients)
scores(PFcompUZL_h_rda, choices = 1:4, display = "bp", scaling = 0)
scores(PFcompUZL_h_rda)
Many thanks for your answer
Sibylle
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