xml_discretetraitmodel: Generate the discrete-geography model block in a BEAST XML...
In jsigao/prioritree: A utility for improving phylodynamic analyses in BEAST

xml_discretetraitmodel

R Documentation

Generate the discrete-geography model block in a BEAST XML file.

Description

Generate the discrete-geography model block in a BEAST XML file.

Usage

xml_discretetraitmodel(
  states_dat,
  discrete_trait_name,
  symmetry = T,
  bssvs = T,
  delta_prior = c("Poisson", "Uniform", "Beta-Binomial"),
  poisson_default = T,
  poisson_mean = 0,
  alpha_beta = 0,
  beta_beta = 0,
  rates_proposal_weight = 0,
  indicators_proposal_weight = 0,
  rootfreq_proposal_weight = 0,
  indicatorprob_proposal_weight = 0
)

Arguments

`states_dat`	a data-frame object containing at least two columns: one for the name of each tip (column name specified by `taxon_name`), and the other for the trait state of each tip (column name specified by `discrete_trait_name`)
`discrete_trait_name`	name of the column containing tip states
`symmetry`	Whether the specified geographic model is symmetric (true) or asymmetric (false)
`bssvs`	Whether Bayesian Stochastic Search Variable Selection (BSSVS) is used (default true) in the discrete-geographic model.
`delta_prior`	Which of the three prior options to put on Δ, including: "Poisson": a(n offset) Poisson distribution (the default option); "Uniform": a uniform distribution between zero and the maximum Δ (when all the dispersal routes exist), and; "Beta-Binomial": a Beta-Binomial distribution.
`poisson_default`	Whether to specify the default Poisson prior in BEAUti.
`poisson_mean`	The rate parameter (λ) of the Poisson distribution.
`alpha_beta`	Parameter α of the Beta-Binomial distribution.
`beta_beta`	Parameter β of the Beta-Binomial distribution.
`rates_proposal_weight`	Weight of the proposals on the pairwise rates of dispersal.
`indicators_proposal_weight`	Weight of the proposals on the indicator variables.
`rootfreq_proposal_weight`	Weight of the proposal on the root-frequency vector.
`indicatorprob_proposal_weight`	Weight of the proposal on the parameter that specifies the probability of each indicator being non-zero (only relevant when `delta_prior` is "Beta-Binomial").