Testing Hardy-Weinberg Equilibrium for Multiallelic Genes
HW.pval calculates plain and fully conditional
root-mean-square, chi-square, and log likelihood-ratio P-values
for the user-provided genotypic counts to be consistent with
the Hardy-Weinberg equilibrium model.  For further information
on the Hardy-Weinberg equilibrium model and the pseudocode,
refer to the paper "Testing Hardy-Weinberg equilibrium with a
simple root-mean-square statistic" by Rachel Ward.

Bayesian investigation of Hardy-Weinberg Equilibrium via
estimation and testing.
Estimation and testing of HWE using Bayesian methods.
Three models are currently considered: HWE, a model
parameterized in terms of the allele frequencies and a single
inbreeding coeffcient \eqn{f}, and the saturated model. Testing
is based on Bayes factors.

Estimation and testing of HWE using Bayesian methods.
Three models are currently considered: HWE, a model
parameterized in terms of the allele frequencies and a single
inbreeding coefficient f, and the saturated model. Testing is
based on Bayes factors.

c(person("Jon", "Wakefield", role = c("aut", "cre"),
email = "jonno@u.washington.edu"),
person("Martyn", "Plummer", role="ctb"))
Jon Wakefield [aut, cre],
Martyn Plummer [ctb]

Objective Bayesian Testing for the Hardy-Weinberg Equilibrium
Problem
This package implements the general (multiallelic)
Hardy-Weinberg equilibrium problem from an objective Bayesian
testing standpoint. This aim is achieved through the
identification of a class of priors specifically designed for
this testing problem. A class of intrinsic priors under the
full model is considered. This class is indexed by a tuning
quantity, the training sample size, as discussed in Consonni,
Moreno and Venturini (2010). These priors are objective,
satisfy Savage's continuity condition and have proved to behave
extremely well for many statistical testing problems.

General (multi-allelic) Hardy-Weinberg equilibrium problem from an objective Bayesian testing standpoint. This aim is achieved through the identification of a class of priors specifically designed for this testing problem. A class of intrinsic priors under the full model is considered. This class is indexed by a tuning quantity, the training sample size, as discussed in Consonni, Moreno and Venturini (2010). These priors are objective, satisfy Savage's continuity condition and have proved to behave extremely well for many statistical testing problems.