Quoting Martin Maechler <[EMAIL PROTECTED]>: > I don't know what exactly you want.
The Gower coefficient I am referring to comes from his 1971 article in Biometrics (27(4):857-871). It differs from most commonly used measures (but not, apparently, daisy!) by allowing the incorporation of quantitative and qualitative (binary or unordered multistate characters) variables, and also by providing a mechanism for dropping missing values from similarity calculations. This is also covered in Legendre and Legendre. > > The function daisy() in the recommended package "cluster" > has always worked with missing values and IIRC, the book > "Kaufman & Rousseeuw" {which I have not at hand here at home}, > clearly mentions Gower's origin of their distance measure > definition. I was unaware of the daisy function. Looking over it now it differs from the Gower coefficient primarily in the method of standardization. Gower standardized each variable by dividing it by it's range ("ranging"), where daisy does a more conventional standardization (-mean and /SD). As I understand it, there isn't much to recommend standardizing over ranging (or vice versa) so daisy may provide a useful alternative for my project. I'll have to look into it! Thanks, Tyler > > Martin Maechler, maintainer of cluster package, > ETH Zurich > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html