primarycensored_ode.stan

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real dist_lcdf(real delay, array[] real params, int dist_id) {
  if (delay <= 0) return negative_infinity();
 
  // IDs match pcd_distributions$stan_id in R
  if (dist_id == 1) return lognormal_lcdf(delay | params[1], params[2]);
  else if (dist_id == 2) return gamma_lcdf(delay | params[1], params[2]);
  else if (dist_id == 3) return weibull_lcdf(delay | params[1], params[2]);
  else if (dist_id == 4) return exponential_lcdf(delay | params[1]);
  else if (dist_id == 9) return beta_lcdf(delay | params[1], params[2]);
  else if (dist_id == 12) return cauchy_lcdf(delay | params[1], params[2]);
  else if (dist_id == 13) return chi_square_lcdf(delay | params[1]);
  else if (dist_id == 15) return gumbel_lcdf(delay | params[1], params[2]);
  else if (dist_id == 16) return inv_gamma_lcdf(delay | params[1], params[2]);
  else if (dist_id == 17) return logistic_lcdf(delay | params[1], params[2]);
  else if (dist_id == 18) return normal_lcdf(delay | params[1], params[2]);
  else if (dist_id == 19) return inv_chi_square_lcdf(delay | params[1]);
  else if (dist_id == 20) return double_exponential_lcdf(delay | params[1], params[2]);
  else if (dist_id == 21) return pareto_lcdf(delay | params[1], params[2]);
  else if (dist_id == 22) return scaled_inv_chi_square_lcdf(delay | params[1], params[2]);
  else if (dist_id == 23) return student_t_lcdf(delay | params[1], params[2], params[3]);
  else if (dist_id == 24) return uniform_lcdf(delay | params[1], params[2]);
  else if (dist_id == 25) return von_mises_lcdf(delay | params[1], params[2]);
  else reject("Invalid distribution identifier: ", dist_id);
}
 
real primary_lpdf(real x, int primary_id, array[] real params, real xmin, real xmax) {
  // Implement switch for different primary distributions
  if (primary_id == 1) return uniform_lpdf(x | xmin, xmax);
  if (primary_id == 2) return expgrowth_lpdf(x | xmin, xmax, params[1]);
  // Add more primary distributions as needed
  reject("Invalid primary distribution identifier");
}
 
vector primarycensored_ode(real t, vector y, array[] real theta,
                            array[] real x_r, array[] int x_i) {
  real d = x_r[1];
  int dist_id = x_i[1];
  int primary_id = x_i[2];
  real pwindow = x_r[2];
  int dist_params_len = x_i[3];
  int primary_params_len = x_i[4];
 
  // Extract distribution parameters
  array[dist_params_len] real params;
  if (dist_params_len) {
    params = theta[1:dist_params_len];
  }
  array[primary_params_len] real primary_params;
  if (primary_params_len) {
    int primary_loc = num_elements(theta);
    primary_params = theta[primary_loc - primary_params_len + 1:primary_loc];
  }
 
  real log_cdf = dist_lcdf(t | params, dist_id);
  real log_primary_pdf = primary_lpdf(d - t | primary_id, primary_params, 0, pwindow);
 
  return rep_vector(exp(log_cdf + log_primary_pdf), 1);
}