Automatic Differentiation
 
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cauchy_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_CAUCHY_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_CAUCHY_LPDF_HPP
3
18#include <cmath>
19
20namespace stan {
21namespace math {
22
40template <bool propto, typename T_y, typename T_loc, typename T_scale,
42 T_y, T_loc, T_scale>* = nullptr>
43return_type_t<T_y, T_loc, T_scale> cauchy_lpdf(const T_y& y, const T_loc& mu,
44 const T_scale& sigma) {
45 using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
46 using std::log;
47 using T_y_ref = ref_type_if_not_constant_t<T_y>;
48 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
49 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
50 static constexpr const char* function = "cauchy_lpdf";
51 check_consistent_sizes(function, "Random variable", y, "Location parameter",
52 mu, "Scale parameter", sigma);
53 T_y_ref y_ref = y;
54 T_mu_ref mu_ref = mu;
55 T_sigma_ref sigma_ref = sigma;
56
57 if (size_zero(y, mu, sigma)) {
58 return 0.0;
59 }
61 return 0.0;
62 }
63
64 T_partials_return logp(0.0);
65 auto ops_partials = make_partials_propagator(y_ref, mu_ref, sigma_ref);
66
67 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
68 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
69 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
70 check_not_nan(function, "Random variable", y_val);
71 check_finite(function, "Location parameter", mu_val);
72 check_positive_finite(function, "Scale parameter", sigma_val);
73
74 size_t N = max_size(y, mu, sigma);
75
76 const auto& inv_sigma
77 = to_ref_if<!is_constant_all<T_scale>::value>(inv(sigma_val));
78 const auto& y_minus_mu
79 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>(y_val - mu_val);
80
81 logp -= sum(log1p(square(y_minus_mu * inv_sigma)));
83 logp -= N * LOG_PI;
84 }
86 logp -= sum(log(sigma_val)) * N / math::size(sigma);
87 }
88
90 const auto& sigma_squared
91 = to_ref_if<!is_constant_all<T_scale>::value>(square(sigma_val));
92 const auto& y_minus_mu_squared
93 = to_ref_if<!is_constant_all<T_scale>::value>(square(y_minus_mu));
97 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
100 partials<0>(ops_partials) = -mu_deriv;
101 } else {
102 partials<0>(ops_partials)[0] = -sum(mu_deriv);
103 }
104 }
106 partials<1>(ops_partials) = std::move(mu_deriv);
107 }
108 }
110 partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared)
111 * inv_sigma
112 / (sigma_squared + y_minus_mu_squared);
113 }
114 }
115 return ops_partials.build(logp);
116}
117
118template <typename T_y, typename T_loc, typename T_scale>
120 const T_loc& mu,
121 const T_scale& sigma) {
122 return cauchy_lpdf<false>(y, mu, sigma);
123}
124
125} // namespace math
126} // namespace stan
127#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 > cauchy_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
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
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition size_zero.hpp:19
T to_ref_if(T &&a)
No-op that should be optimized away.
Definition to_ref.hpp:29
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
static constexpr double LOG_PI
The natural logarithm of , .
Definition constants.hpp:86
fvar< T > log1p(const fvar< T > &x)
Definition log1p.hpp:12
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.
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.
fvar< T > square(const fvar< T > &x)
Definition square.hpp:12
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 ...
If the input type T is either an eigen matrix with 1 column or 1 row at compile time or a standard ve...
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...