ThetaMater.PPS: ThetaMater.PPS: function to simulate posterior predictive...

In radamsRHA/ThetaMater: ThetaMater: Bayesian estimation of the population size parameter theta from genomic data

ThetaMater.PPS: function to simulate posterior predictive distributions of mutation counts using the posterior distributions estimated using ThetaMater

Description

This function returns a vector of mutation counts for every simulated locus (the posterior predictive distribution)

Usage

ThetaMater.PPS(theta.MCMC, l.vec, n.vec)

Arguments

theta.MCMC	MCMC chain sampling of theta parameter provided by ThetaMater
l.vec	Vector of locus lengths
n.vec	Vector of sample numbers

Examples

sim.results <- Coal.Theta.Sim.File(theta = .9/10, n.vec = c(5,5), l.vec = c(100,100), num.loci = 1000, out.file = '~/Desktop/example.alleles')
example.data <- Read.AllelesFile.Threshold(alleles.file = '~/Desktop/example.alleles', threshold = 1000, log.file = '~/Desktop/log.txt')
Theta.Posterior <- ThetaMater.M3(k.vec = example.data$k.vec, l.vec = example.data$l.vec, n.vec = example.data$n.vec, c.vec = example.data$c.vec, ngens = 10000)

radamsRHA/ThetaMater documentation built on April 25, 2024, 10:11 a.m.