20241209_Bayesian_class

data.json

{
  "a0": 0.700102,
  "b0": 1,
  "N": 94,
  "k": 8
}

main.stan

data {
  real<lower = 0> a0;
  real<lower = 0> b0;
  int<lower = 1> N; // total number of infections
  int<lower = 0, upper = N> k; // number of infections among vaccinated
}
parameters {
  real<lower = 0, upper = 1> theta;
}
transformed parameters {
  real<lower = -1, upper = 1> VE = (1 - 2 * theta) / (1 - theta);
}
model {
  theta ~ beta(a0, b0);
  //target += beta_lpdf(theta | a0, b0);
  k ~ binomial(N, theta);
}
generated quantities {
  int k_pred = binomial_rng(N, theta);
}

meta.json

{"title":"Untitled"}

sampling_opts.json

{"num_chains":4,"num_warmup":1000,"num_samples":1000,"init_radius":2}