model {
   # allele frequencies into genotype frequenices
   p.SS <- p.s*p.s + f*p.s*(1-p.s)
   p.SM <- 2*p.s*p.m*(1-f) 
   p.SF <- 2*p.s*p.f*(1-f)
   p.SO <- 2*p.s*p.o*(1-f)
   p.MM <- p.m*p.m + f*p.m*(1-p.m)
   p.MF <- 2*p.m*p.f*(1-f)
   p.MO <- 2*p.m*p.o*(1-f)
   p.FF <- p.f*p.f + f*p.f*(1-p.f)
   p.FO <- 2*p.f*p.o*(1-f)
   p.OO <- p.o*p.o + f*p.o*(1-p.o)

   # genotype frequencies into phenotype frequencies
   pi[1] <- p.SS + p.SO
   pi[2] <- p.SM
   pi[3] <- p.SF
   pi[4] <- p.MM + p.MO
   pi[5] <- p.MF
   pi[6] <- p.FF + p.FO
   pi[7] <- p.OO
   
   # The likelihood
   n[1:7] ~ dmulti(pi[], N)

   # priors
   # allele frequencies
   for (i in 1:4) {
      phi[i] ~ dgamma(1, 1)
   }
   p.s <- phi[1]/sum(phi[])
   p.m <- phi[2]/sum(phi[])
   p.f <- phi[3]/sum(phi[])
   p.o <- phi[4]/sum(phi[])
   # f
   w ~ dunif(0,1);
   s.f <- max(-p.s/(1-p.s), -(1-p.s)/p.s)
   m.f <- max(-p.m/(1-p.m), -(1-p.m)/p.m)
   f.f <- max(-p.f/(1-p.f), -(1-p.f)/p.f)
   o.f <- max(-p.o/(1-p.o), -(1-p.o)/p.o)
   min.f.1 <- max(s.f, m.f)
   min.f.2 <- max(f.f, o.f)
   f.min <- max(min.f.1, min.f.2)
   f <- w*(1 - f.min) + f.min

   # sample size
   N <- sum(n[])
}

# data
list(n=c(1149, 336, 203, 36, 25, 17, 20))