ThetaMater.M0: ThetaMater.M0: (Bayesian Model 1) Simple MCMC algorithm to...

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

ThetaMater.M0: (Bayesian Model 1) Simple MCMC algorithm to estimate the posteriori distribution of theta from genomic data

Description

This function returns a list of each step in the MCMC sampling chain

Usage

ThetaMater.M0(k.vec, l.vec, n.vec, c.vec, ngens)

Arguments

k.vec	Vector of mutation counts
l.vec	Vector of locus lengths
n.vec	Vector of sample numbers
c.vec	Vector of data pattern counts
ngens	Number of generations to run the MCMC

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 <- MCMC.Theta.M1.R(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.