get_ML_state_indices

A row from a <code>relprobs</code>, a
  numeric matrix of relative probabilities

relprobs_row

Numbers indexing the states from 1 to
  numstates

nums

The value of the maximum probability for
  the row.

maxprob

What to do with ties. Currently, the only
  option is to take the first (this will be shown in e.g. a
  pie chart, of course).

if_ties


  Given a table with the rows representing nodes, and the
  columns representing the relative probabilities of each
  state, this function finds the ML (maximum likelihood)
  state(s) for each node;
  <code><a rd-options="" href="/link/get_ML_state_indices?package=BioGeoBEARS&version=0.2.1" data-mini-rdoc="BioGeoBEARS::get_ML_state_indices">get_ML_state_indices</a></code> does this for a row,
  <code><a rd-options="" href="/link/get_ML_states?package=BioGeoBEARS&version=0.2.1" data-mini-rdoc="BioGeoBEARS::get_ML_states">get_ML_states</a></code> iterates over all the rows.


BioGeoBEARS allows probabilistic inference of both historical biogeography (ancestral geographic ranges on a phylogeny) as well as comparison of different models of range evolution.  It reproduces the model available in LAGRANGE (Ree and Smith 2008), as well as making available numerous additional models. For example, LAGRANGE as typically run has two free parameters, d (dispersal rate, i.e. the rate of range addition along a phylogenetic branch) and e (extinction rate, really the rate of local range loss along a phylogenetic branch). LAGRANGE also has a fixed cladogenic model which gives equal probability to a number of allowed range inheritance events, e.g.: (1) vicariance, (2) a new species starts in a subset of the ancestral range, (3) the ancestral range is copied to both species; in all cases, at least one species must have a starting range of size 1.  LAGRANGE assigns equal probability to each of these events, and zero probability to other events.  BioGeoBEARS adds an additional cladogenic event: founder-event speciation (the new species jumps to a range outside of the ancestral range), and also allows the relative weighting of the different sorts of events to be made into free parameters, allowing optimization and standard model choice procedures to pick the best model. The relative probability of different descendent range sizes is also parameterized and thus can also be specified or estimated.  The flexibility available in BioGeoBEARS also enables the natural incorporation of (1) imperfect detection of geographic ranges in the tips, and (2) inclusion of fossil geographic range data, when the fossils are tips on the phylogeny. Bayesian analysis has been implemented through use of the "LaplacesDemon" package, however this package is now maintained off of CRAN, so its usage is not formally included in BioGeoBEARS at the current time.  CITATION INFO: This package is the result of my Ph.D. research, please cite the package if you use it!  Type: citation(package="BioGeoBEARS") to get the citation information.

get_ML_state_indices: Extract the indices for the ML states at each node, given a row of relative probabilities

Description

Usage

Arguments

Value

References

See Also

Examples