1#ifndef STAN_MATH_PRIM_PROB_FRECHET_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_FRECHET_LPDF_HPP
18#include <boost/random/weibull_distribution.hpp>
19#include <boost/random/variate_generator.hpp>
28template <
bool propto,
typename T_y,
typename T_shape,
typename T_scale,
30 T_y, T_shape, T_scale>* =
nullptr>
33 const T_scale& sigma) {
38 static constexpr const char* function =
"frechet_lpdf";
40 alpha,
"Scale parameter", sigma);
42 T_alpha_ref alpha_ref = alpha;
43 T_sigma_ref sigma_ref = sigma;
67 const auto& sigma_div_y_pow_alpha
68 = to_ref_if<!is_constant_all<T_y, T_shape, T_scale>::value>(
69 pow(sigma_val / y_val, alpha_val));
71 size_t N =
max_size(y, alpha, sigma);
72 T_partials_return logp = -
sum(sigma_div_y_pow_alpha);
77 logp -=
sum((alpha_val + 1.0) * log_y) * N /
max_size(y, alpha);
81 = to_ref_if<!is_constant_all<T_shape>::value>(
log(sigma_val));
82 logp +=
sum(alpha_val * log_sigma) * N /
max_size(alpha, sigma);
84 edge<1>(ops_partials).partials_
85 =
inv(alpha_val) + (1 - sigma_div_y_pow_alpha) * (log_sigma - log_y);
89 edge<0>(ops_partials).partials_
90 = (alpha_val * sigma_div_y_pow_alpha - (alpha_val + 1)) / y_val;
93 edge<2>(ops_partials).partials_
94 = alpha_val / sigma_val * (1 - sigma_div_y_pow_alpha);
96 return ops_partials.build(logp);
99template <
typename T_y,
typename T_shape,
typename T_scale>
101 const T_shape& alpha,
102 const T_scale& sigma) {
103 return frechet_lpdf<false>(y, alpha, sigma);
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_lpdf(const T_y_cl &y, const T_shape_cl &alpha, const T_scale_cl &sigma)
The log of the frechet density for the specified scalar(s) given the specified sample stan::math::siz...
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>>.
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
T to_ref_if(T &&a)
No-op that should be optimized away.
auto pow(const T1 &x1, const T2 &x2)
fvar< T > log(const fvar< T > &x)
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.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
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.
fvar< T > inv(const fvar< T > &x)
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< true, T >::type ref_type_t
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...