Compute average trees or consensus trees by various criteria.
averageTree(trees, start=NULL, method="quadratic.path.difference",
tol=1e-12, quiet=FALSE, ...)
ls.consensus(trees, start=NULL, tol=1e-12, quiet=FALSE, ...)
minTreeDist(tree, trees, method="quadratic.path.difference", ...)
An object of class "phylo"
with edge lengths.
object of class "multiPhylo"
.
object of class "phylo"
. For minTreeDist
the tree on which to find the edge lengths that minimize the distance to the phylogenies in trees
.
starting tree for optimization.
distance criterion for minimization. Options are "symmetric.difference"
, "branch.score.difference"
, "path.difference"
, and "quadratic.path.difference"
.
tolerance value for optimization.
logical value indicating whether to run "quietly" or not.
other arguments to be passed internally.
Liam Revell liam.revell@umb.edu
The function averageTree
tries to find the (hypothetical) tree topology and branch lengths that has a minimum distance to all the trees in an input set, according to some user-specified tree distance measure.
The function ls.consensus
computes the least-squares consensus tree (Lapointe & Cucumel, 1997) from a set of input trees.
Finally, the function minTreeDist
finds the tree in the input set that is a minimum distance to all the other trees in the set. (This contrasts with averageTree
which can return a tree not in the input set.)
Lapointe, F.-J., G. Cucumel (1997) The average consensus procedure: Combination of weighted trees containing identical or overlapping sets of taxa. Systematic Biology, 46, 306-312.
Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.