M2s2596860.jags

     # Defining the updated Bayesian model with same set of
     # hyperparameters

model {
     # Initialization of the prior parameters tau and tau_o
     tau ~ dgamma(4,0.04)
     tau_o ~ dgamma(4,0.04)
     
     # Calculating x values by iterating through each experiment
     for (j in 1:n_experiments) {
     
     # Initializing x[1,j] and x[2,j] with normal distributions
       x[1,j] ~ dnorm(0,100)
       x[2,j] ~ dnorm(x[1,j],tau)
       
       #Iterating through remaining doses for each experiment
       for (i in 3:n_doses) {
         x[i,j] ~ dnorm(2* x[i-1,j] - x[i-2,j],tau)
        }
      }
    
    # Calculating m and mu values for each experiment and dose
    for(j in 1:n_experiments) {
      m[1,j] <- 0
      mu[1,j] <- 1
      
      # Iterating through doses for each experiment to
      # calculate m and mu values
      for (i in 2:n_doses) {
        m[i,j] <- m[i-1,j]-exp(x[i-1,j])
        mu[i,j] <- exp(m[i,j])
      }
    }
    
    # Modelling the effect for each dose in every experiment
    for (j in 1:n_experiments) {
    
    # Prior for Mj parameter following an uniform distribution
      Mj[j] ~ dunif(0,4000) 
      for (i in 1:n_doses) {
      
      # Model for effect[i,j] for each experiment and dose
        effect[i,j] ~ dnorm(Mj[j] * mu[i,j] , tau_o)
    }
  }
}