poisson_binomial_lpmf.hpp

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#ifndef STAN_MATH_PRIM_PROB_POISSON_BINOMIAL_LPMF_HPP
#define STAN_MATH_PRIM_PROB_POISSON_BINOMIAL_LPMF_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/max_size.hpp>
#include <stan/math/prim/fun/scalar_seq_view.hpp>
#include <stan/math/prim/fun/poisson_binomial_log_probs.hpp>
#include <stan/math/prim/fun/vector_seq_view.hpp>
 
namespace stan {
namespace math {
 
template <bool propto, typename T_y, typename T_theta>
return_type_t<T_theta> poisson_binomial_lpmf(const T_y& y,
                                             const T_theta& theta) {
  static constexpr const char* function = "poisson_binomial_lpmf";
 
  size_t size_theta = size_mvt(theta);
  if (size_theta > 1) {
    check_consistent_sizes(function, "Successes variables", y,
                           "Probability parameters", theta);
  }
 
  size_t max_sz = std::max(stan::math::size(y), size_theta);
  scalar_seq_view<T_y> y_vec(y);
  vector_seq_view<T_theta> theta_vec(theta);
 
  for (size_t i = 0; i < max_sz; ++i) {
    check_bounded(function, "Successes variable", y_vec[i], 0,
                  theta_vec[i].size());
    check_finite(function, "Probability parameters", theta_vec.val(i));
    check_bounded(function, "Probability parameters", theta_vec.val(i), 0.0,
                  1.0);
  }
 
  return_type_t<T_theta> log_prob = 0.0;
  for (size_t i = 0; i < max_sz; ++i) {
    auto x = poisson_binomial_log_probs(y_vec[i], theta_vec[i]);
    log_prob += x(y_vec[i]);
  }
 
  return log_prob;
}
 
template <typename T_y, typename T_theta>
return_type_t<T_theta> poisson_binomial_lpmf(const T_y& y,
                                             const T_theta& theta) {
  return poisson_binomial_lpmf<false>(y, theta);
}
 
}  // namespace math
}  // namespace stan
#endif