Automatic Differentiation
 
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skew_normal_rng.hpp
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1#ifndef STAN_MATH_PRIM_PROB_SKEW_NORMAL_RNG_HPP
2#define STAN_MATH_PRIM_PROB_SKEW_NORMAL_RNG_HPP
3
11#include <boost/random/normal_distribution.hpp>
12#include <boost/random/variate_generator.hpp>
13
14namespace stan {
15namespace math {
16
39template <typename T_loc, typename T_scale, typename T_shape, class RNG>
41skew_normal_rng(const T_loc& mu, const T_scale& sigma, const T_shape& alpha,
42 RNG& rng) {
43 using boost::variate_generator;
44 using boost::random::normal_distribution;
45 static constexpr const char* function = "skew_normal_rng";
46 check_consistent_sizes(function, "Location parameter", mu, "Scale Parameter",
47 sigma, "Shape Parameter", alpha);
48 if (size_zero(mu, sigma, alpha)) {
49 return {};
50 }
51 const auto& mu_ref = to_ref(mu);
52 const auto& sigma_ref = to_ref(sigma);
53 const auto& alpha_ref = to_ref(alpha);
54 check_finite(function, "Location parameter", mu_ref);
55 check_positive_finite(function, "Scale parameter", sigma_ref);
56 check_finite(function, "Shape parameter", alpha_ref);
57
58 scalar_seq_view<T_loc> mu_vec(mu_ref);
59 scalar_seq_view<T_scale> sigma_vec(sigma_ref);
60 scalar_seq_view<T_shape> alpha_vec(alpha_ref);
61 size_t N = max_size(mu, sigma, alpha);
63
64 variate_generator<RNG&, normal_distribution<> > norm_rng(
65 rng, normal_distribution<>(0, 1));
66 for (size_t n = 0; n < N; ++n) {
67 double r1 = norm_rng();
68 double r2 = norm_rng();
69
70 if (r2 > alpha_vec[n] * r1) {
71 r1 = -r1;
72 }
73
74 output[n] = mu_vec[n] + sigma_vec[n] * r1;
75 }
76
77 return output.data();
78}
79
80} // namespace math
81} // namespace stan
82#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, double, T_loc, T_scale, T_shape >::type skew_normal_rng(const T_loc &mu, const T_scale &sigma, const T_shape &alpha, RNG &rng)
Return a Skew-normal random variate for the given location, scale, and shape using the specified rand...
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition size_zero.hpp:19
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.
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:18
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.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...