LambdaPriorChoice {HWEBayes} | R Documentation |
Internal function, should not be needed. It is the function that is minmized when the mean and standard deviation for λ 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