aceArbor : function

collection: ancestralStates

Overview

aceArbor is a function for carrying out ancestral state reconstruction. It works for both discrete and continuous variables, and can reconstruct ancestral character states under both a maximum-likelihood and a Bayesian framework. The function returns results in two formats: a table of ancestral state estimates for each node in the tree, and a plot of the results.

Example

From the docs page, get anolis.phy and anolis.csv. Load these files into Arbor, and use them as inputs to the aceArbor function. Choose the “ecomorph” column for analysis, and select type: discrete and method: marginal.

Arguments

• table: A data table including species names
• tree: A phylogenetic tree
• column: The name of the column to analyze
• type: The character type
  • discrete: a character with a discrete number of states
  • continuous: a continuously varying character
  • fromData: will attempt to determine the data type from the data itself
• method: specifies the method used to reconstruct ancestral character states
  • marginal: marginal ancestral state reconstructions, which reconstruct each node integrating over all possibilities at all other nodes in the tree; this is typically the method used in the literature to reconstruce ACEs
  • joint: joint ancestral reconstructions, which give the configuration of ancestral states that together maximize the likelihood of the data given model parameters
  • mcmc: reconstruct ancestral states using Bayesian MCMC. Note that the discrete version of this doesn’t seem to work, and even if it did work it is not a full MCMC ancestral state method
  • stochastic: create stochastic character map

Outputs

Function outputs a table and a plot with results of the ancestral state reconstruction.

References