Automatic Differentiation
 
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frechet_cdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_FRECHET_CDF_HPP
2#define STAN_MATH_PRIM_PROB_FRECHET_CDF_HPP
3
13#include <cmath>
14
15namespace stan {
16namespace math {
17
18template <typename T_y, typename T_shape, typename T_scale,
20 T_y, T_shape, T_scale>* = nullptr>
22 const T_shape& alpha,
23 const T_scale& sigma) {
24 using T_partials_return = partials_return_t<T_y, T_shape, T_scale>;
25 using T_y_ref = ref_type_t<T_y>;
26 using T_alpha_ref = ref_type_t<T_shape>;
27 using T_sigma_ref = ref_type_t<T_scale>;
28 using std::pow;
29 static constexpr const char* function = "frechet_cdf";
30 T_y_ref y_ref = y;
31 T_alpha_ref alpha_ref = alpha;
32 T_sigma_ref sigma_ref = sigma;
33
34 check_positive(function, "Random variable", y_ref);
35 check_positive_finite(function, "Shape parameter", alpha_ref);
36 check_positive_finite(function, "Scale parameter", sigma_ref);
37
38 if (size_zero(y_ref, alpha_ref, sigma_ref)) {
39 return 1.0;
40 }
41
42 T_partials_return cdf(1.0);
43 auto ops_partials = make_partials_propagator(y_ref, alpha_ref, sigma_ref);
44
45 scalar_seq_view<T_y> y_vec(y_ref);
46 scalar_seq_view<T_scale> sigma_vec(sigma_ref);
47 scalar_seq_view<T_shape> alpha_vec(alpha_ref);
48 size_t N = max_size(y_ref, sigma_ref, alpha_ref);
49
50 for (size_t n = 0; n < N; n++) {
51 const T_partials_return y_dbl = y_vec.val(n);
52 const T_partials_return sigma_dbl = sigma_vec.val(n);
53 const T_partials_return alpha_dbl = alpha_vec.val(n);
54 const T_partials_return pow_n = pow(sigma_dbl / y_dbl, alpha_dbl);
55 const T_partials_return cdf_n = exp(-pow_n);
56
57 cdf *= cdf_n;
58
59 if constexpr (is_autodiff_v<T_y>) {
60 partials<0>(ops_partials)[n] += pow_n * alpha_dbl / y_dbl;
61 }
62 if constexpr (is_autodiff_v<T_shape>) {
63 partials<1>(ops_partials)[n] += pow_n * log(y_dbl / sigma_dbl);
64 }
65 if constexpr (is_autodiff_v<T_scale>) {
66 partials<2>(ops_partials)[n] -= pow_n * alpha_dbl / sigma_dbl;
67 }
68 }
69
70 if constexpr (is_autodiff_v<T_y>) {
71 for (size_t n = 0; n < stan::math::size(y); ++n) {
72 partials<0>(ops_partials)[n] *= cdf;
73 }
74 }
75 if constexpr (is_autodiff_v<T_shape>) {
76 for (size_t n = 0; n < stan::math::size(alpha); ++n) {
77 partials<1>(ops_partials)[n] *= cdf;
78 }
79 }
80 if constexpr (is_autodiff_v<T_scale>) {
81 for (size_t n = 0; n < stan::math::size(sigma); ++n) {
82 partials<2>(ops_partials)[n] *= cdf;
83 }
84 }
85 return ops_partials.build(cdf);
86}
87
88} // namespace math
89} // namespace stan
90#endif
scalar_seq_view provides a uniform sequence-like wrapper around either a scalar or a sequence of scal...
require_all_not_t< is_nonscalar_prim_or_rev_kernel_expression< std::decay_t< Types > >... > require_all_not_nonscalar_prim_or_rev_kernel_expression_t
Require none of the types satisfy is_nonscalar_prim_or_rev_kernel_expression.
return_type_t< T_y_cl, T_shape_cl, T_scale_cl > frechet_cdf(const T_y_cl &y, const T_shape_cl &alpha, const T_scale_cl &sigma)
Returns the frechet cumulative distribution function for the given location, and scale.
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
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition size_zero.hpp:19
auto pow(const T1 &x1, const T2 &x2)
Definition pow.hpp:32
fvar< T > log(const fvar< T > &x)
Definition log.hpp:18
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
void check_positive_finite(const char *function, const char *name, const T_y &y)
Check if y is positive and finite.
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:15
typename ref_type_if< true, T >::type ref_type_t
Definition ref_type.hpp:56
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 ...