LambdaPriorChoice {HWEBayes} | R Documentation |
Internal function, should not be needed. It is the function that is minmized when the mean and standard deviation for \lambda are being found.
LambdaPriorChoice(x, nsim, bvec, f1, f2, p1, p2, init)
x |
Proposal for lambdamu and exp(lambdasd ).
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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
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init |
initial values for lambdamu and lambdasd
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Returns the sum of squares that is being minimized.
Jon Wakefield (jonno@u.washington.edu)
Wakefield, J. (2009). Bayesian methods for examining Hardy-Weinberg equilibrium. Biometrics.
LambdaOptim