TreeSearch (version 0.4.0)

IWScoreMorphy: Profile Parsimony Score

Description

Calculate a tree's Profile Parsimony score with a given dataset, after Faith and Trueman (2001).

Usage

IWScoreMorphy(parent, child, dataset, concavity = 10L,
  minLength = attr(dataset, "min.length"), ...)
ProfileScore(tree, dataset)
ProfileScoreMorphy(parent, child, dataset, ...)
ProfileInitMorphy(dataset)
ProfileDestroyMorphy(dataset)

Arguments

parent

Integer vector corresponding to the first column of the edge matrix of a tree of class phylo, i.e. tree$edge[, 1].

child

Integer vector corresponding to the second column of the edge matrix of a tree of class phylo, i.e. tree$edge[, 2].

dataset

Dataset of class phyDat. The dataset should have been prepared using dataset <- PrepareDataProfile(dataset); if this step has not been completed, the dataset will be (time-consumingly) prepared within the function. In subsidiary functions, the dataset will have been initialized using ProfileInitMorphy, must be destroyed using ProfileDestroyMorphy.

concavity

A numeric value to use as the concavity constant (k) in implied weighting. Defaults to 10; TNT sets a default of 3, but this is too low in some circumstances (Smith, 2019).

minLength

Integer vector specifying the minimum length possible for each character in dataset, perhaps calculated using MinimumLength.

…

unused; allows additional parameters specified within … to be received by the function without throwing an error.

tree

A tree of class phylo.

Value

Zero minus the profile score (because the optimization algorithm treats smaller numbers as better)

Functions

• IWScoreMorphy: Scorer for Implied Weighting dataset.

• ProfileScoreMorphy: Scorer for initialized dataset.

• ProfileInitMorphy: Initialize dataset by adding morphyObjs attribute.

• ProfileDestroyMorphy: Free memory from morphyObjs initialized by ProfileScoreMorphy().

References

Faith2001TreeSearch

Examples

# NOT RUN {
  data(referenceTree)
  data(congreveLamsdellMatrices)
  # In actual use, the dataset should be prepared with a much higher
  # precision: try 1e+06?
  # Of course, gaining higher precision takes substantially longer.
  dataset <- suppressWarnings(
    PrepareDataProfile(congreveLamsdellMatrices[[42]], precision = 1e+03))
  ProfileScore(referenceTree, dataset)

# }