Automatic Differentiation
 
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poisson_binomial_lccdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_POISSON_BINOMIAL_LCCDF_HPP
2#define STAN_MATH_PRIM_PROB_POISSON_BINOMIAL_LCCDF_HPP
3
13
14namespace stan {
15namespace math {
16
30template <bool propto, typename T_y, typename T_theta>
32 const T_theta& theta) {
33 static constexpr const char* function = "poisson_binomial_lccdf";
34
35 auto size_theta = size_mvt(theta);
36 if (size_theta > 1) {
37 check_consistent_sizes(function, "Successes variables", y,
38 "Probability parameters", theta);
39 }
40
41 auto max_sz = std::max(stan::math::size(y), size_mvt(theta));
42 scalar_seq_view<T_y> y_vec(y);
43 vector_seq_view<T_theta> theta_vec(theta);
44
45 for (size_t i = 0; i < max_sz; ++i) {
46 check_bounded(function, "Successes variable", y_vec[i], 0,
47 theta_vec[i].size());
48 check_finite(function, "Probability parameters", theta_vec.val(i));
49 check_bounded(function, "Probability parameters", theta_vec.val(i), 0.0,
50 1.0);
51 }
52
53 return_type_t<T_theta> lccdf = 0.0;
54 for (size_t i = 0; i < max_sz; ++i) {
55 if (stan::math::size(theta_vec[i]) == 1) {
56 if (y_vec[i] == 0) {
57 lccdf += log(theta_vec[i][0]);
58 } else {
59 lccdf -= stan::math::INFTY;
60 }
61 } else {
62 auto x = log1m_exp(
63 log_sum_exp(poisson_binomial_log_probs(y_vec[i], theta_vec[i])));
64 lccdf += x;
65 }
66 }
67 return lccdf;
68}
69
70template <typename T_y, typename T_theta>
72 const T_theta& theta) {
73 return poisson_binomial_lccdf<false>(y, theta);
74}
75
76} // namespace math
77} // namespace stan
78#endif
scalar_seq_view provides a uniform sequence-like wrapper around either a scalar or a sequence of scal...
This class provides a low-cost wrapper for situations where you either need an Eigen Vector or RowVec...
return_type_t< T_theta > poisson_binomial_lccdf(const T_y &y, const T_theta &theta)
Returns the log CCDF for the Poisson-binomial distribution evaluated at the specified number of succe...
int64_t size_mvt(const ScalarT &)
Provides the size of a multivariate argument.
Definition size_mvt.hpp:25
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
int64_t size(const T &m)
Returns the size (number of the elements) of a matrix_cl or var_value<matrix_cl<T>>.
Definition size.hpp:19
void check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Check if the value is between the low and high values, inclusively.
Eigen::Matrix< T_scalar, -1, 1 > poisson_binomial_log_probs(int y, const T_theta &theta)
Returns the last row of the log probability matrix of the Poisson-Binomial distribution given the num...
fvar< T > log1m_exp(const fvar< T > &x)
Return the natural logarithm of one minus the exponentiation of the specified argument.
Definition log1m_exp.hpp:22
fvar< T > log(const fvar< T > &x)
Definition log.hpp:18
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
void check_finite(const char *function, const char *name, const T_y &y)
Return true if all values in y are finite.
static constexpr double INFTY
Positive infinity.
Definition constants.hpp:44
fvar< T > log_sum_exp(const fvar< T > &x1, const fvar< T > &x2)
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...