Automatic Differentiation
 
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gumbel_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_GUMBEL_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_GUMBEL_LPDF_HPP
3
17#include <cmath>
18
19namespace stan {
20namespace math {
21
37template <bool propto, typename T_y, typename T_loc, typename T_scale,
39 T_y, T_loc, T_scale>* = nullptr>
40return_type_t<T_y, T_loc, T_scale> gumbel_lpdf(const T_y& y, const T_loc& mu,
41 const T_scale& beta) {
42 using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
43 using T_y_ref = ref_type_if_not_constant_t<T_y>;
44 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
45 using T_beta_ref = ref_type_if_not_constant_t<T_scale>;
46 static constexpr const char* function = "gumbel_lpdf";
47 check_consistent_sizes(function, "Random variable", y, "Location parameter",
48 mu, "Scale parameter", beta);
49 T_y_ref y_ref = y;
50 T_mu_ref mu_ref = mu;
51 T_beta_ref beta_ref = beta;
52
53 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
54 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
55 decltype(auto) beta_val = to_ref(as_value_column_array_or_scalar(beta_ref));
56
57 check_not_nan(function, "Random variable", y_val);
58 check_finite(function, "Location parameter", mu_val);
59 check_positive(function, "Scale parameter", beta_val);
60
61 if (size_zero(y, mu, beta)) {
62 return 0.0;
63 }
65 return 0.0;
66 }
67
68 auto ops_partials = make_partials_propagator(y_ref, mu_ref, beta_ref);
69
70 const auto& inv_beta
71 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>(inv(beta_val));
72 const auto& y_minus_mu_over_beta = to_ref((y_val - mu_val) * inv_beta);
73 const auto& exp_y_m_mu_over_beta
74 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>(
75 exp(-y_minus_mu_over_beta));
76
77 size_t N = max_size(y, mu, beta);
78 T_partials_return logp = -sum(y_minus_mu_over_beta + exp_y_m_mu_over_beta);
80 logp -= sum(log(beta_val)) * N / math::size(beta);
81 }
82
84 const auto& scaled_diff
85 = to_ref_if<!is_constant_all<T_loc>::value
88 >= 2>(inv_beta * exp_y_m_mu_over_beta - inv_beta);
90 partials<0>(ops_partials) = scaled_diff;
91 }
93 partials<1>(ops_partials) = -scaled_diff;
94 }
96 edge<2>(ops_partials).partials_
97 = -y_minus_mu_over_beta * scaled_diff - inv_beta;
98 }
99 }
100 return ops_partials.build(logp);
101}
102
103template <typename T_y, typename T_loc, typename T_scale>
105 const T_loc& mu,
106 const T_scale& beta) {
107 return gumbel_lpdf<false>(y, mu, beta);
108}
109
110} // namespace math
111} // namespace stan
112#endif
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_loc_cl, T_scale_cl > gumbel_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &beta)
Returns the Gumbel log probability density for the given location and scale.
size_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:18
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
size_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_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
fvar< T > log(const fvar< T > &x)
Definition log.hpp:15
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.
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:22
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
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_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
fvar< T > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
Definition beta.hpp:51
fvar< T > inv(const fvar< T > &x)
Definition inv.hpp:12
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:13
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 ...
Definition fvar.hpp:9
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...