Claddis (version 0.3.4)

GetAllStateChanges: Finds all state changes on a tree using stochastic character mapping

Description

Takes a cladistic matrix and time-scaled tree and makes point estimates for every character change using stochastic character mapping.

Usage

GetAllStateChanges(CladisticMatrix, Tree, TimeBins, NSimulations = 10,
  PolymorphismBehaviour = "equalp", UncertaintyBehaviour = "equalp",
  InapplicableBehaviour = "missing")

Arguments

CladisticMatrix

A character-taxon matrix in the format imported by ReadMorphNexus.

Tree

A time-scaled tree (phylo object) that represents the relationships of the taxa in CladisticMatrix.

TimeBins

A vector of ages representing the boundaries of a series of time bins.

NSimulations

The number of simulations to perform (passed to make.simmap.

PolymorphismBehaviour

What to do with polymorphic (&) characters. One of "equalp", "missing", or "random". See details.

UncertaintyBehaviour

What to do with uncertain (/) characters. One of "equalp", "missing", or "random". See details.

InapplicableBehaviour

What to do with inapplicable characters. Only one option currently ("missing"). See details.

Value

RootStates

A matrix of the root states for each character (column) and simulation (rows).

AllStateChanges

A matrix of rows for each change with columns corresponding to the character, the simulation number, the edge number, the time the change occurred, and the start and end states.

CharacterTimes

A vector of the sampled tree-length (in Ma) for each character.

EdgeLengthsPerBin

A matrix of time bins (columns) and characters (rows) indicating the sampled tree-length (in Ma).

TerminalEdgeLengthsPerBin

As above, but for terminal edges only.

InternalEdgeLengthsPerBin

As above, but for internal edges only.

Details

Important: this function is not yet complete and should not be used.

A wrapper function for make.simmap in the phytools package.

This function is intended to enumerate all possible changes on a tree (including to and from missing or inapplicable states) under the assumptions of stochastic character mapping as an alternative means of establishing branch-lengths (for rate analyses) or recording the state occupied at a particular point in time for disparity analyses.

Examples

# NOT RUN {
# Set random seed:
set.seed(2)

# Use Day 2016 as source matrix:
CladisticMatrix <- Day2016

# Prune out continuous characters:
CladisticMatrix <- MatrixPruner(CladisticMatrix =
  CladisticMatrix, blocks2prune = 1)

# Prune out majority of characters so
# example runs quickly:
CladisticMatrix <- MatrixPruner(CladisticMatrix =
  CladisticMatrix, characters2prune = 1:32)

# Generete random tree for matrix taxa:
Tree <- rtree(nrow(Day2016$Matrix_1$Matrix))

# Add taxon names to tree:
Tree$tip.label <- rownames(Day2016$Matrix_1$Matrix)

# Add root age to tree:
Tree$root.time <- max(diag(vcv(Tree)))

# Get all state changes for two simulations:
StateChanges <-
  GetAllStateChanges(CladisticMatrix = CladisticMatrix,
  Tree = Tree, TimeBins = seq(Tree$root.time, 0,
  length.out = 3), NSimulations = 2)

# View matrix of all stochstic character changes:
StateChanges$AllStateChanges

# View vector of sampled time for each
# character:
StateChanges$CharacterTimes

# View matrix of edge lengths in each time bin:
StateChanges$EdgeLengthsPerBin

# View matrix of termnial edge lengths in each time bin:
StateChanges$TerminalEdgeLengthsPerBin

# View matrix of internal edge lengths in each time bin:
StateChanges$InternalEdgeLengthsPerBin

# }