# Samples from the single f prior.

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### Description

Function to sample from the single f prior, that is the Dirichlet and normal on λ, where λ=\log((f-f_{\min})/(1-f)).

### Usage

 `1` ```SinglefPrior(nsim, alpha, lambdamu, lambdasd) ```

### Arguments

 `nsim` number of simulations from prior `alpha` vector of k parameters for the Dirichlet prior on the k allele frequencies. `lambdamu` mean of the normal prior on λ. `lambdasd` standard deviation of the normal prior on λ.

### Value

 `p` sample for vector of k allele frequencies `f` sample of f parameters `lgts` samples for logits of baseline logits `lambda` samples for λ

### Author(s)

Jon Wakefield (jonno@u.washington.edu)

### References

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

`SinglefReject`, `HWEsimdat`
 ```1 2``` ```SinglefSamp <- SinglefPrior(nsim=1000,alpha=c(1,1,1,1), lambdamu=-2.95,lambdasd=1.07) ```