Ratchet bootstrapper
MorphyBootstrap(edgeList, morphyObj, EdgeSwapper = NNISwap, maxIter,
maxHits, verbosity = 1L, stopAtPeak = FALSE, stopAtPlateau = 0L,
...)ProfileBootstrap(edgeList, dataset, EdgeSwapper = NNISwap, maxIter,
maxHits, verbosity = 1L, ...)
IWBootstrap(edgeList, dataset, concavity = 4L, EdgeSwapper = NNISwap,
maxIter, maxHits, verbosity = 1L, ...)
a list containing the following: - vector of integers corresponding to the parent of each edge in turn - vector of integers corresponding to the child of each edge in turn - (optionally) score of the tree - (optionally, if score provided) number of times this score has been hit
A morphy object, perhaps created with PhyDat2Morphy.
a function that rearranges a parent and child vector,
and returns a list with modified vectors; for example
SPRSwap.
maximum number of iterations to perform in tree search
maximum number of hits to accomplish in tree search
Level of detail to display in console: larger numbers provide more verbose feedback to the user.
Logical specifying whether to terminate search once a subsequent
iteration recovers a sub-optimal score. Useful with methods that
return all trees one rearrangement from the current tree, such
as AllTBR. Will be overridden if a passed function
has an attribute stopAtPeak set by
attr(FunctionName, 'stopAtPeak') <- TRUE.
Integer. If > 0, tree search will terminate if the score
has not improved after stopAtPlateau iterations.
Useful with methods that return all trees one
rearrangement from the current tree, such as
AllTBR.
Will be overridden if a passed function has an attribute
stopAtPlateau set by attr(FunctionName, 'stopAtPlateau') <- TRUE.
further parameters to send to TreeScorer
A phylogenetic data matrix of class phyDat,
whose names correspond to the labels of any accompanying tree.
A numeric value to use as the concavity constant (k) in implied weighting.
A tree that is optimal under a random sampling of the original characters
ProfileBootstrap: Bootstrapper for Profile Parsimony
IWBootstrap: Bootstrapper for Implied weighting