  In this article the results of Waddell and Azad (2009) are extended. In
particular, the geometric percentage mean standard deviation measure of the fit
of distances to a phylogenetic tree is adjusted for the number of parameters
fitted to the model. The formulae are also presented in their general form for
any weight that is a function of the distance. The cell line gene expression
data set of Ross et al. (2000) is reanalyzed. It is shown that ordinary least
squares (OLS) is a much better fit to the data than a Neighbor Joining or BME
tree. Residual resampling shows that cancer cell lines do indeed fit a tree
fairly well and that the tree does have strong internal structure. Simulations
show that least squares tree building methods, including OLS, are strong
competitors with BME type methods for fitting model data, while real world
examples often suggest the same conclusion.
