sim.island.model: Simulate Artificial Data from an Island Model

In infeR: A pedagogical tool to teach the basics of inference in population genetics

Description

Simulate artificial data using the coalescent, and return summary statistics from each dataset.

Usage

  sim.island.model(number.of.simulations,mutation.model,total.number.of.demes,number.of.loci,number.of.sampled.demes,sample.sizes)

Arguments

number.of.simulations	total number of simulations
mutation.model	a character string indicating the mutation model. Possible values are "IAM" (infinite island model),"KAM" (K-allele model) and "SMM" (stepwise mutation model)
total.number.of.demes	total number of demes in the island model
number.of.loci	total number of simulated loci
number.of.sampled.demes	number of demes sampled
sample.sizes	number of genes sampled in each deme

Details

Simulate artificial data using a coalescent-based simulator, and return summary statistics from each dataset.

Value

a matrix of summary statistics.

Examples

## This is to generate a prior distribution of the model parameters.

prior <- generate.prior(number.of.simulations = 1e3,prior.theta = 'UNI',min.theta = 0.1, max.theta = 5,prior.M = 'UNI',min.M = 0.1,max.M = 5)

## This is to generate summary statistics from simulated data.

stats <- sim.island.model(number.of.simulations = 1e3,mutation.model = 'SMM',total.number.of.demes = 10,number.of.loci = 20,number.of.sampled.demes = 10,sample.sizes = 50)

stats

infeR documentation built on May 2, 2019, 4:45 p.m.