Automatic Differentiation
 
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pareto_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_PARETO_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_PARETO_LPDF_HPP
3
18#include <cmath>
19
20namespace stan {
21namespace math {
22
23// Pareto(y|y_m, alpha) [y > y_m; y_m > 0; alpha > 0]
24template <bool propto, typename T_y, typename T_scale, typename T_shape,
26 T_y, T_scale, T_shape>* = nullptr>
28 const T_scale& y_min,
29 const T_shape& alpha) {
30 using T_partials_return = partials_return_t<T_y, T_scale, T_shape>;
31 using T_y_ref = ref_type_if_not_constant_t<T_y>;
32 using T_y_min_ref = ref_type_if_not_constant_t<T_scale>;
33 using T_alpha_ref = ref_type_if_not_constant_t<T_shape>;
34 static constexpr const char* function = "pareto_lpdf";
35 check_consistent_sizes(function, "Random variable", y, "Scale parameter",
36 y_min, "Shape parameter", alpha);
37 if (size_zero(y, y_min, alpha)) {
38 return 0;
39 }
40
41 T_y_ref y_ref = y;
42 T_y_min_ref y_min_ref = y_min;
43 T_alpha_ref alpha_ref = alpha;
44
45 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
46 decltype(auto) y_min_val = to_ref(as_value_column_array_or_scalar(y_min_ref));
47 decltype(auto) alpha_val = to_ref(as_value_column_array_or_scalar(alpha_ref));
48
49 check_not_nan(function, "Random variable", y_val);
50 check_positive_finite(function, "Scale parameter", y_min_val);
51 check_positive_finite(function, "Shape parameter", alpha_val);
52
54 return 0;
55 }
56
57 if (sum(promote_scalar<int>(y_val < y_min_val))) {
58 return LOG_ZERO;
59 }
60
61 const auto& log_y = to_ref_if<!is_constant_all<T_shape>::value>(log(y_val));
62
63 size_t N = max_size(y, y_min, alpha);
64 T_partials_return logp(0);
66 logp = sum(log(alpha_val)) * N / math::size(alpha);
67 }
69 logp -= sum(alpha_val * log_y + log_y) * N / max_size(alpha, y);
70 }
71
72 auto ops_partials = make_partials_propagator(y_ref, y_min_ref, alpha_ref);
74 const auto& inv_y = inv(y_val);
75 edge<0>(ops_partials).partials_
76 = -(alpha_val * inv_y + inv_y) * N / max_size(alpha, y);
77 }
79 edge<1>(ops_partials).partials_
80 = alpha_val / y_min_val * N / max_size(alpha, y_min);
81 }
83 const auto& log_y_min
84 = to_ref_if<!is_constant_all<T_shape>::value>(log(y_min_val));
85 logp += sum(alpha_val * log_y_min) * N / max_size(alpha, y_min);
87 partials<2>(ops_partials) = inv(alpha_val) + log_y_min - log_y;
88 }
89 }
90
91 return ops_partials.build(logp);
92}
93
94template <typename T_y, typename T_scale, typename T_shape>
96 const T_scale& y_min,
97 const T_shape& alpha) {
98 return pareto_lpdf<false>(y, y_min, alpha);
99}
100
101} // namespace math
102} // namespace stan
103#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_scale_cl, T_shape_cl > pareto_lpdf(const T_y_cl &y, const T_scale_cl &y_min, const T_shape_cl &alpha)
The log of the Cauchy density for the specified scalar(s) given the specified location parameter(s) a...
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
static constexpr double LOG_ZERO
The natural logarithm of 0, .
Definition constants.hpp:68
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
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:23
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
fvar< T > inv(const fvar< T > &x)
Definition inv.hpp:13
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.
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...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...