model{
    for(ti in 1:10){
      mu[ti] <- A*exp(-b*exp(-c*ti))
    }
    for(i in 1:n){
      y[i] ~ dnorm(mu[t[i]], tau)
    }
    A ~ dnorm(0, 0.00001)T(0,)  #
    b ~ dnorm(0, 0.05)T(0,)     # precision = 1/variance
    c ~ dnorm(0, 1)T(0,)        #
    tau ~ dgamma(0.01, 0.01)
  }