Automatic Differentiation
 
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neg_binomial_2_log_rng.hpp
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1#ifndef STAN_MATH_PRIM_PROB_NEG_BINOMIAL_2_LOG_RNG_HPP
2#define STAN_MATH_PRIM_PROB_NEG_BINOMIAL_2_LOG_RNG_HPP
3
9#include <boost/random/gamma_distribution.hpp>
10#include <boost/random/poisson_distribution.hpp>
11#include <boost/random/variate_generator.hpp>
12#include <cmath>
13
14namespace stan {
15namespace math {
16
35template <typename T_loc, typename T_inv, class RNG>
37neg_binomial_2_log_rng(const T_loc& eta, const T_inv& phi, RNG& rng) {
38 using boost::gamma_distribution;
39 using boost::variate_generator;
40 using boost::random::poisson_distribution;
41 using T_eta_ref = ref_type_t<T_loc>;
42 using T_phi_ref = ref_type_t<T_inv>;
43 static constexpr const char* function = "neg_binomial_2_log_rng";
44 check_consistent_sizes(function, "Log-location parameter", eta,
45 "Inverse dispersion parameter", phi);
46 T_eta_ref eta_ref = eta;
47 T_phi_ref phi_ref = phi;
48 check_finite(function, "Log-location parameter", eta_ref);
49 check_positive_finite(function, "Inverse dispersion parameter", phi_ref);
50
51 scalar_seq_view<T_eta_ref> eta_vec(eta_ref);
52 scalar_seq_view<T_phi_ref> phi_vec(phi_ref);
53 size_t N = max_size(eta, phi);
55
56 for (size_t n = 0; n < N; ++n) {
57 double exp_eta_div_phi
58 = std::exp(static_cast<double>(eta_vec[n])) / phi_vec[n];
59
60 // gamma_rng params must be positive and finite
61 check_positive_finite(function,
62 "Exponential of the log-location parameter "
63 "divided by the precision parameter",
64 exp_eta_div_phi);
65
66 double rng_from_gamma = variate_generator<RNG&, gamma_distribution<> >(
67 rng, gamma_distribution<>(phi_vec[n], exp_eta_div_phi))();
68
69 // same as the constraints for poisson_rng
70 check_less(function, "Random number that came from gamma distribution",
71 rng_from_gamma, POISSON_MAX_RATE);
72 check_not_nan(function, "Random number that came from gamma distribution",
73 rng_from_gamma);
74 check_nonnegative(function,
75 "Random number that came from gamma distribution",
76 rng_from_gamma);
77
78 output[n] = variate_generator<RNG&, poisson_distribution<> >(
79 rng, poisson_distribution<>(rng_from_gamma))();
80 }
81
82 return output.data();
83}
84
85} // namespace math
86} // namespace stan
87#endif
typename helper::type type
VectorBuilder allocates type T1 values to be used as intermediate values.
scalar_seq_view provides a uniform sequence-like wrapper around either a scalar or a sequence of scal...
VectorBuilder< true, int, T_loc, T_inv >::type neg_binomial_2_log_rng(const T_loc &eta, const T_inv &phi, RNG &rng)
Return a negative binomial random variate with the specified log-location and inverse dispersion para...
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
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.
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
void check_less(const char *function, const char *name, const T_y &y, const T_high &high, Idxs... idxs)
Throw an exception if y is not strictly less than high.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
void check_positive_finite(const char *function, const char *name, const T_y &y)
Check if y is positive and finite.
typename ref_type_if< true, T >::type ref_type_t
Definition ref_type.hpp:55
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...