data {
  // The input data are: 
  // the sample size (constrain to be >= 1) 
  // the vector 'complaints' (of length 'N') 
  // the vector 'traps' (of length 'N')  
}
parameters {
 // Our model  accepts two parameters 'alpha' and 'beta'
}
model {
  // weakly informative priors:
  // we expect negative slope on traps and a positive intercept,
  // so for alpha a N(log(4), 1) and for beta a N(-0.25, 1)
 
  // likelihood: Consider poisson_log(eta), which is  more efficient and stable alternative to poisson(exp(eta))
  
}