Hi All, I am using canonical correspondence analysis to compare a community composition matrix to a matrix of sample spatial relationships and environmental variables. In order to parse out how much variance is explained purely by space (S/E) or the environment (E/S) I am using a conditional (partial) CCA. I want to test significance via Monte Carlo but I can not find a way to do this with a conditional CCA. I have been using vegan for the CCA and attempting to use ade4 to run a Monte Carlo. However, these two packages conflict when it comes to CCA. If I use vegan I can run a conditional CCA, and if I use ade4 I can do a Monte Carlo - but I can't figure out how to do a conditional CCA with ade4 OR a Monte Carlo with vegan. If anyone has experience with this I would be truly grateful for your help! I am fairly new to R, and I have quickly found myself in a place where "Google-ing" has no longer proven useful. Below are my scripts and error messages.
Using Vegan: > vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) + > Condition(Env2)..., HabitatSpaceR.csv) > randtest(vare.cca, nrepet = 1000) Error in randtest.cca(vare.cca, nrepet = 1000) : Object of class dudi expected Using ade4: > vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) + > Condition(Env2)..., HabitatSpaceR.csv) Error in cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) + Condition(Env2)... + : data.frame expected -- View this message in context: http://r.789695.n4.nabble.com/Conditional-CCA-and-Monte-Carlo-Help-tp4662572.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.
