Automatic Differentiation
 
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weibull_lccdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_WEIBULL_LCCDF_HPP
2#define STAN_MATH_PRIM_PROB_WEIBULL_LCCDF_HPP
3
15#include <cmath>
16
17namespace stan {
18namespace math {
19
34template <typename T_y, typename T_shape, typename T_scale,
36 T_y, T_shape, T_scale>* = nullptr>
38 const T_shape& alpha,
39 const T_scale& sigma) {
40 using T_partials_return = partials_return_t<T_y, T_shape, T_scale>;
41 using T_y_ref = ref_type_if_not_constant_t<T_y>;
42 using T_alpha_ref = ref_type_if_not_constant_t<T_shape>;
43 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
44 using std::pow;
45 static constexpr const char* function = "weibull_lccdf";
46
47 T_y_ref y_ref = y;
48 T_alpha_ref alpha_ref = alpha;
49 T_sigma_ref sigma_ref = sigma;
50
51 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
52 decltype(auto) alpha_val = to_ref(as_value_column_array_or_scalar(alpha_ref));
53 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
54
55 check_nonnegative(function, "Random variable", y_val);
56 check_positive_finite(function, "Shape parameter", alpha_val);
57 check_positive_finite(function, "Scale parameter", sigma_val);
58
59 if (size_zero(y, alpha, sigma)) {
60 return 0.0;
61 }
62
63 auto ops_partials = make_partials_propagator(y_ref, alpha_ref, sigma_ref);
64
65 const auto& pow_n = to_ref_if<!is_constant_all<T_y, T_shape, T_scale>::value>(
66 pow(y_val / sigma_val, alpha_val));
67 T_partials_return ccdf_log = -sum(pow_n);
68
70 partials<0>(ops_partials) = -alpha_val / y_val * pow_n;
71 }
73 partials<1>(ops_partials) = -log(y_val / sigma_val) * pow_n;
74 }
76 partials<2>(ops_partials) = alpha_val / sigma_val * pow_n;
77 }
78 return ops_partials.build(ccdf_log);
79}
80
81} // namespace math
82} // namespace stan
83#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_shape_cl, T_scale_cl > weibull_lccdf(const T_y_cl &y, const T_shape_cl &alpha, const T_scale_cl &sigma)
Returns the weibull log cumulative complementary distribution function for the given location,...
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
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
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...
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:23
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...