abc_smc: abc function

In thijsjanzen/enviDiv:

abc function

Description

abc function

Usage

abc_smc(
  ref_tree,
  statistics,
  simulation_function,
  init_epsilon_value,
  prior_generating_function,
  prior_density_function,
  number_of_particles = 1000,
  sigma = 0.05,
  stop_rate = 1e-05,
  num_iterations = 50
)

Arguments

statistics	A list containing statistics functions
simulation_function	A function that implements the diversification model and returns an object of class "phylo".
prior_generating_function	Function to generate parameters from the prior distribution of these parameters (e.g. a function returning lambda and mu in case of the birth-death model)
prior_density_function	Function to calculate the prior probability of a set of parameters.
number_of_particles	Number of particles to be used per iteration of the ABC-SMC algorithm.
sigma	Standard deviation of the perturbance distribution (perturbance distribution is a gaussian with mean 0).
stop_rate	If the acceptance rate drops below stopRate, stop the ABC-SMC algorithm and assume convergence.
num_iterations	num iterations
tree	an object of class "phylo"; the tree upon which we want to fit our diversification model
init_epsilon_values	A vector containing the initial threshold values for the summary statistics from the vector statistics.

Value

A matrix with n columns, where n is the number of parameters you are trying to estimate.

References

Toni, T., Welch, D., Strelkowa, N., Ipsen, A., & Stumpf, M.P.H. (2009). Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society Interface, 6(31), 187-202.

thijsjanzen/enviDiv documentation built on Feb. 17, 2025, 8:20 p.m.