sim.coexpPT: Simulation of codemographic models

In gehara/PipeMaster: Building and Simulating Coalescent models.

Simulation of codemographic models

Description

Simulation of the PT model of Gehara et al. (2017)

Usage

sim.coexpPT(
  nsims,
  var.zeta,
  coexp.prior,
  Ne.prior,
  NeA.prior,
  time.prior,
  gene.prior,
  alpha = F,
  append.sims = F,
  path = getwd()
)

Arguments

nsims	Total number of simulations
var.zeta	Variation on zeta parameter. Can be "FREE" to vary or be set to a specific value (between 0-1).
coexp.prior	Uniform prior for the coespansion time. Vector of two numbers with the lower and upper boudary of the prior.
Ne.prior	Data frame with the prior values for the Ne of each population.
NeA.prior	Data frame with the prior values for the ancestral Ne of each population.
time.prior	Data frame with parameter values for the priors of the time of demographic change of each population.
gene.prior	Data frame with parameter values for the priors of the mutation rate of each species.
alpha	logical. If TRUE all demographic chages are exponential. If FALSE sudden changes. Defaut is FALSE.
append.sims	logical. If TRUE simulations are appended to the simulations file. Defaut is FALSE.
path	Path to the directiry to write the simulations. Defaut is the working directory.

Details

To simulate the model of Chan et al. (2014), the Threshold model and the Narrow Coexpansion Time model use the sim.coexp function.

See references for more details.

References

Gehara M., Garda A.A., Werneck F.P. et al. (2017) Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil. Molecular Ecology, 26, 4756–4771.

Chan Y.L., Schanzenbach D., & Hickerson M.J. (2014) Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation. Molecular Biology and Evolution, 31, 2501–2515.

gehara/PipeMaster documentation built on April 19, 2024, 8:14 a.m.