gibbs_known: Gibbs sampler under random mating with known genotypes.

In hwep: Hardy-Weinberg Equilibrium in Polyploids

Gibbs sampler under random mating with known genotypes.

Description

Gibbs sampler under random mating with known genotypes.

Usage

gibbs_known(x, alpha, B = 10000L, T = 1000L, more = FALSE, lg = FALSE)

Arguments

x	The vector of genotype counts. x(i) is the number of individuals that have genotype i.
alpha	Vector of hyperparameters for the gamete frequencies. Should be length (x.length() - 1) / 2 + 1.
B	The number of sampling iterations.
T	The number of burn-in iterations.
more	A logical. Should we also return posterior draws (TRUE) or not (FALSE).
lg	Should we return the log marginal likelihood (true) or not (false).

Value

A list with some or all of the following elements

• mx: The estimate of the marginal likelihood

• p_tilde: The value of p used to evaluate the posterior density.

• p: The samples of the gamete frequencies

• post: The likelihood times prior evaluated at current samples.

• ptilde_post: The samples of the full conditionals of p_tilde.

Author(s)

David Gerard

hwep documentation built on May 31, 2023, 9:06 p.m.