Bayes test for random mating with known genotypes

rmbayes(
  nvec,
  lg = TRUE,
  alpha = NULL,
  beta = NULL,
  nburn = 10000,
  niter = 10000,
  type = c("auto", "allo")
)

Arguments

nvec: A vector containing the observed genotype counts, where nvec[[i]] is the number of individuals with genotype i-1. This should be of length ploidy+1.
lg: A logical. Should we return the log Bayes factor (TRUE) or the Bayes factor (FALSE)?
alpha: The concentration hyperparameters of the gamete frequencies under the null of random mating. Should be length ploidy/2 + 1.
beta: The concentration hyperparameters of the genotype frequencies under the alternative of no random mating. Should be length ploidy + 1.
nburn: The number of iterations in the Gibbs sampler to burn-in.
niter: The number of sampling iterations in the Gibbs sampler.
type: If alpha is NULL, then the default priors depend on if you have autopolyploids ("auto") or allopolyploids ("allo").

References

Gerard D (2023). "Bayesian tests for random mating in polyploids." Molecular Ecology Resources, In press. doi:10.1111/1755-0998.13856 .

Author

David Gerard

Examples

set.seed(1)
ploidy <- 8

## Simulate under the null
p <- stats::runif(ploidy / 2 + 1)
p <- p / sum(p)
q <- stats::convolve(p, rev(p), type = "open")

## See BF increase
nvec <- c(stats::rmultinom(n = 1, size = 100, prob = q))
rmbayes(nvec = nvec)
#> [1] 2.122218

nvec <- c(stats::rmultinom(n = 1, size = 1000, prob = q))
rmbayes(nvec = nvec)
#> [1] 8.487987

nvec <- c(stats::rmultinom(n = 1, size = 10000, prob = q))
rmbayes(nvec = nvec)
#> [1] 11.77032

## Simulate under the alternative
q <- stats::runif(ploidy + 1)
q <- q / sum(q)

## See BF decrease
nvec <- c(stats::rmultinom(n = 1, size = 100, prob = q))
rmbayes(nvec = nvec)
#> [1] -11.87659

nvec <- c(stats::rmultinom(n = 1, size = 1000, prob = q))
rmbayes(nvec = nvec)
#> [1] -128.9095

nvec <- c(stats::rmultinom(n = 1, size = 10000, prob = q))
rmbayes(nvec = nvec)
#> [1] -1265.442