abcRej: Approximate Bayesian Computation inference via Rejection...

In ercrema/cTransmission: An Approximate Bayesian Computation framework for inferring patterns of cultural transmission from frequency data

Description

Estimates model parameter via Approximate Bayesian Computation.

Usage

abcRej(x, sim.model, prior, nsim, tol, ncore = 1)

Arguments

x	A cFreqData class object with the observed variant frequencies.
sim.model	A transmission model generated using the genSim() function.
prior	A list of model priors. Each element of the list corresponds to a model parameter. The list element must be a vector whose first argument determines the type of prior distribution: possible values are "unif" for a uniform distribution on a segment and "normal" for a normal distribution. The following arguments of the list elements contain the characteritiscs of the prior distribution chosen: for "unif", two numbers must be given: the minimum and maximum values of the uniform distribution; for "normal", two numbers must be given: the mean and standard deviation of the normal distribution. Syntax adapted from the EasyABC package.
nsim	Number of simulations
tol	Required proportion of accepted simulations.
ncore	Number of cores for parallel processing. Default is 1.

ercrema/cTransmission documentation built on May 15, 2020, 4:42 a.m.