Automatic Differentiation
 
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poisson_lccdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_POISSON_LCCDF_HPP
2#define STAN_MATH_PRIM_PROB_POISSON_LCCDF_HPP
3
21#include <cmath>
22#include <limits>
23
24namespace stan {
25namespace math {
26
27template <typename T_n, typename T_rate>
28return_type_t<T_rate> poisson_lccdf(const T_n& n, const T_rate& lambda) {
29 using T_partials_return = partials_return_t<T_n, T_rate>;
30 using T_n_ref = ref_type_if_not_constant_t<T_n>;
31 using T_lambda_ref = ref_type_if_not_constant_t<T_rate>;
32 static constexpr const char* function = "poisson_lccdf";
33 check_consistent_sizes(function, "Random variable", n, "Rate parameter",
34 lambda);
35
36 T_n_ref n_ref = n;
37 T_lambda_ref lambda_ref = lambda;
38
39 decltype(auto) n_val = to_ref(as_value_column_array_or_scalar(n_ref));
40 decltype(auto) lambda_val
42
43 check_nonnegative(function, "Rate parameter", lambda_val);
44
45 if (size_zero(n, lambda)) {
46 return 0;
47 }
48
49 auto ops_partials = make_partials_propagator(lambda_ref);
50
51 if (sum(promote_scalar<int>(n_val < 0))) {
52 return ops_partials.build(0.0);
53 }
54
55 const auto& log_Pi = to_ref_if<!is_constant_all<T_rate>::value>(
56 log(gamma_p(n_val + 1.0, lambda_val)));
57 T_partials_return P = sum(log_Pi);
58
60 partials<0>(ops_partials) = exp(n_val * log(lambda_val) - lambda_val
61 - lgamma(n_val + 1.0) - log_Pi);
62 }
63
64 return ops_partials.build(P);
65}
66
67} // namespace math
68} // namespace stan
69#endif
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition size_zero.hpp:19
fvar< T > log(const fvar< T > &x)
Definition log.hpp:18
auto as_value_column_array_or_scalar(T &&a)
Extract the value from an object and for eigen vectors and std::vectors convert to an eigen column ar...
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
Definition lgamma.hpp:21
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition gamma_p.hpp:18
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:23
return_type_t< T_rate > poisson_lccdf(const T_n &n, const T_rate &lambda)
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:15
typename ref_type_if<!is_constant< T >::value, T >::type ref_type_if_not_constant_t
Definition ref_type.hpp:62
typename partials_return_type< Args... >::type partials_return_t
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...