Tree search using successive approximations

Searches for a tree that is optimal under the Successive Approximations criterion (Farris 1969) .

Usage

SuccessiveApproximations(
  tree,
  dataset,
  outgroup = NULL,
  k = 3,
  maxSuccIter = 20,
  ratchetHits = 100,
  searchHits = 50,
  searchIter = 500,
  ratchetIter = 5000,
  verbosity = 0,
  suboptimal = 0.1
)

SuccessiveWeights(tree, dataset)

Arguments

tree

A tree of class phylo.

dataset

A phylogenetic data matrix of phangorn class phyDat, whose names correspond to the labels of any accompanying tree.

outgroup

if not NULL, taxa on which the tree should be rooted

k

Constant for successive approximations, see Farris 1969 p. 379

maxSuccIter

maximum iterations of successive approximation

ratchetHits

maximum hits for parsimony ratchet

searchHits

maximum hits in tree search

searchIter

maximum iterations in tree search

ratchetIter

maximum iterations of parsimony ratchet

verbosity

Numeric specifying level of detail to display in console: larger numbers provide more verbose feedback to the user.

suboptimal

retain trees that are this proportion less optimal than the optimal tree

Value

SuccessiveApproximations() returns a list of class multiPhylo containing optimal (and slightly suboptimal, if suboptimal > 0) trees.

SuccessiveWeights() returns the score of a tree, given the weighting instructions specified in the attributes of the dataset.

References

Farris JS (1969). “A successive approximations approach to character weighting.” Systematic Biology, 18(4), 374–385. doi:10.2307/2412182 .

See also

Other custom search functions: EdgeListSearch(), Jackknife(), MorphyBootstrap()