LambdaPriorChoice {HWEBayes}R Documentation

Called by LambaOptim

Description

Internal function, should not be needed. It is the function that is minmized when the mean and standard deviation for λ are being found.

Usage

LambdaPriorChoice(x, nsim, bvec, f1, f2, p1, p2, init)

Arguments

x Proposal for lambdamu and exp(lambdasd).
nsim number of points to simulate from the prior
bvec k vector of Dirichlet prior parameters.
f1 first quantile for inbreeding coefficient f
f2 second quantile for inbreeding coefficient f
p1 probability associated with f1
p2 probability associated with f2
init initial values for lambdamu and lambdasd

Value

Returns the sum of squares that is being minimized.

Author(s)

Jon Wakefield (jonno@u.washington.edu)

References

Wakefield, J. (2009). Bayesian methods for examining Hardy-Weinberg equilibrium. Biometrics.

See Also

LambdaOptim


[Package HWEBayes version 1.0 Index]