model
   {
      for (i in 1 : Dogs) {
         xa[i, 1] <- 0; xs[i, 1] <- 0 p[i, 1] <- 0 
         for (j in 2 : Trials) {
            xa[i, j] <- sum(Y[i, 1 : j - 1])
            xs[i, j] <- j - 1 - xa[i, j]
            log(p[i, j]) <- alpha * xa[i, j] + beta * xs[i, j]
            y[i, j] <- 1 - Y[i, j]
            y[i, j] ~ dbern(p[i, j])
         }
      } 
       alpha ~ dnorm(0, 0.00001)I(, -0.00001)
       beta ~ dnorm(0, 0.00001)I(, -0.00001)
       A <- exp(alpha)
       B <- exp(beta)
   }