I am not sure about your question but i did find this: http://research.med.helsinki.fi/corefacilities/proteinchem/hierarchical_clustering_basics.pdf
it seems to address all three topics so perhaps the answer is in there?? On Mar 28, 2013, at 6:16 PM, Pierre Antoine DuBoDeNa wrote: > Hello, > > I want to use pearson's correlation as distance between observations and > then use any centroid based linkage distance (ex. Ward's distance) > > When linkage distances are formed as the Lance-Williams recursive > formulation, they just require the initial distance between observations. > See here: http://en.wikipedia.org/wiki/Ward%27s_method > > It is said that you have to use euclidean distance between the initial > observations. However i have found this: > > http://research.stowers-institute.org/efg/R/Visualization/cor-cluster/ > > where they use pearson's correlation for hierarchical clustering. > > Any idea if anything is violated in case pearson's correlation is used with > Ward's linkage function? > > the dissimilarity of pearson's correlation can be defined as d = > sqrt(1-pearsonsimilarity^2). can that be considered as norm1 distance? and > thus norm2 if we square it? so that the wikipedia's statement "To apply a > recursive algorithm under this objective function, the initial distance > between individual objects must be (proportional to) squared Euclidean > distance." is valid? > > Best, > Pierre > > [[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. [[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.
