>>>>> "Joe" == Joe Felsenstein <joe at evolution.genetics.washington.edu>
writes: In article <4giqf9$m06 at nntp3.u.washington.edu>
joe at evolution.genetics.washington.edu (Joe Felsenstein) writes:
Joe> In likelihood methods (such as Ziheng Yang's methods that use
Joe> gamma-distributed rates in his PAML package, or my Hidden
Joe> Markov Model approach in DNAML) one can change the rate
Joe> variation parameters until the overall likelihood of the tree
Joe> is maximized. With distance methods, I am not as sure how to
Joe> do this. Perhaps one could try various values until the
Joe> goodness of fit of the tree (say, the sum of squares) is
Joe> optimized, but doing this may have biases in it.
I don't think comparing goodness-of-fit values would work, unless they
were normalized in some way. The distance between sequences A and B
increases as the coefficient of variation increases, so the total tree
length would also increase as the coefficient of variation
increases. It's not obvious to me that there is a scale-invariant way
of comparing the goodness-of-fit statistics, but maybe I'm missing
something. (It wouldn't be the first time.)
-- Kent
--
Kent E. Holsinger Kent at Darwin.EEB.UConn.Edu
-- Department of Ecology & Evolutionary Biology
-- University of Connecticut, U-43
-- Storrs, CT 06269-3043
