Determine best model for ancestral state reconstruction — find_best_asr

Function to find best model for ancestral state reconstruction using corHMM.

Usage

find_best_asr_model(
  df,
  tr,
  tip_name_variable,
  trait,
  node_states = "joint",
  upper_bound = 1e+50,
  lower_bound = 1e-09
)

df: Dataframe with tip name (e.g., tip_name_variable) and phenotype/trait (e.g., trait) variables
tr: Phylogeny object of class "phylo"
tip_name_variable: Name of variable containing tip names in the dataframe (df). Tip name variable must correspond to tip names in the tree.
trait: Name of phenotype/trait variable in the dataframe (df).
node_states: Perform "joint" or "marginal" reconstruction. Default: joint
upper_bound: Upper bound for likelihood search. Default: 1e50
lower_bound: Lower bound for likelihood search. Default: 1e-9

model_statistics: Dataframe with summary of model options
best_model: Character string indicating best model (i.e., "ER" or "ARD)
node_states: Characetr string whether "joint" or "marginal" reconstruction was performed
corHMM_output_best_model: corHMM output for best model