Hello everyone, I mail you because of my lake of knowlegde regarding statistics. I'm using the CA and PCoA (but maybe should I use some other techniques) to determine the differences and similarities between a large sample of plants using different kind of traits through matrix of mixte variables. I understood that the daisy() function using the gower metric and defining the different type of variable is a good way to deal with such mixt variable. And in fact, my plots (cluster{agnes})(more that my PCoA) are quite reflecting what I was expecting from the aspect of those different plants.
My problem : The problem now is that I need to understand wich variables are considered to produce the dissimilarity matrix that is used for the cluster analysis or the PCoA. In other word, "how are construct the branch of my Cluster Analysis tree?" It has been one month since I tried to figured most of the things out of what I know today in "data analysis and R software" world. So, I'm really sorry for asking so simple things that do not exactly focus on the R issues but I tried in many ways but I just can't figure it out. Thank you Julien Mehl Vettori [[alternative HTML version deleted]] ______________________________________________ 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.