HWEmodelsMLE: Evaluates the maximum likelihood estimates of the parameters...

In HWEBayes: Bayesian investigation of Hardy-Weinberg Equilibrium via estimation and testing.

Description

Function to obtain the MLEs of parameters under the HWE, single f and saturated models. For the single f model numerical maximization is required if k>2, where k is the number of alleles.

Usage

HWEmodelsMLE(nvec)

Arguments

nvec	vector of genotype frequencies in the order n_{11}, n_{21}, n_{22}, ..., n_{k1}, n_{k2}, ..., n_{kk}.

Value

phat	matrix of k \times k MLEs of genotype frequencies
qhat	MLEs of k allele frequencies under the HWE model
fqhat	MLEs of k allele frequencies under the single f model
fsingle	MLE of single f
fmaxloglik	maximized log-likelihood (without the normalizing constant), under the single f model
fmin	estimated lower bound of f_{\min} in the single f model. Under the single f model f_{\min} < f <1 where f_{\min}=-p_{\min}/(1-p_{\min}) and p_{\min} is the minimum of the allele frequencies.

Author(s)

Jon Wakefield ([e-mail])

References

Wakefield, J. (2010). Bayesian methods for examining Hardy-Weinberg equilibrium. Biometrics; Vol 66:257-65

Weir, B.S. (1996). Genetic Data Analysis II. Sunderland MA: Sinauer.

Examples

data(DiabRecess)
HWEmodelsMLE(nvec=DiabRecess)

HWEBayes documentation built on May 2, 2019, 11:07 a.m.