data {
  int<lower=0> n;
  int<lower=0> y[n];
  vector[n] x;
  vector[n] e;
}

// The parameters accepted by the model. 
parameters {
  real alpha;
  real beta;
}

// The model to be estimated. We model the output
// 'y' to be normally distributed with mean 'mu'
// and standard deviation 'sigma'.
model {
    y ~ poisson(exp(e+alpha+beta*x));
}

CXXFLAGS = -O2 -ftree-vectorize -march=x86-64 -mtune=generic -fno-math-errno $(LTO)