Automatic Differentiation
 
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student_t_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_STUDENT_T_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_STUDENT_T_LPDF_HPP
3
21#include <cmath>
22
23namespace stan {
24namespace math {
25
55template <bool propto, typename T_y, typename T_dof, typename T_loc,
56 typename T_scale,
58 T_y, T_dof, T_loc, T_scale>* = nullptr>
60 const T_y& y, const T_dof& nu, const T_loc& mu, const T_scale& sigma) {
61 using T_partials_return = partials_return_t<T_y, T_dof, T_loc, T_scale>;
62 using T_y_ref = ref_type_if_not_constant_t<T_y>;
63 using T_nu_ref = ref_type_if_not_constant_t<T_dof>;
64 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
65 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
66 static constexpr const char* function = "student_t_lpdf";
67 check_consistent_sizes(function, "Random variable", y,
68 "Degrees of freedom parameter", nu,
69 "Location parameter", mu, "Scale parameter", sigma);
70 T_y_ref y_ref = y;
71 T_mu_ref mu_ref = mu;
72 T_nu_ref nu_ref = nu;
73 T_sigma_ref sigma_ref = sigma;
74
75 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
76 decltype(auto) nu_val = to_ref(as_value_column_array_or_scalar(nu_ref));
77 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
78 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
79
80 check_not_nan(function, "Random variable", y_val);
81 check_positive_finite(function, "Degrees of freedom parameter", nu_val);
82 check_finite(function, "Location parameter", mu_val);
83 check_positive_finite(function, "Scale parameter", sigma_val);
84
85 if (size_zero(y, nu, mu, sigma)) {
86 return 0.0;
87 }
89 return 0.0;
90 }
91
92 auto ops_partials
93 = make_partials_propagator(y_ref, nu_ref, mu_ref, sigma_ref);
94
95 const auto& half_nu
96 = to_ref_if<include_summand<propto, T_dof>::value>(0.5 * nu_val);
97 const auto& square_y_scaled = square((y_val - mu_val) / sigma_val);
98 const auto& square_y_scaled_over_nu
99 = to_ref_if<is_any_autodiff_v<T_y, T_dof, T_loc, T_scale>>(square_y_scaled
100 / nu_val);
101 const auto& log1p_val
102 = to_ref_if<is_autodiff_v<T_dof>>(log1p(square_y_scaled_over_nu));
103
104 size_t N = max_size(y, nu, mu, sigma);
105 T_partials_return logp = -sum((half_nu + 0.5) * log1p_val);
106 if constexpr (include_summand<propto>::value) {
107 logp -= LOG_SQRT_PI * N;
108 }
110 logp += (sum(lgamma(half_nu + 0.5)) - sum(lgamma(half_nu))
111 - 0.5 * sum(log(nu_val)))
112 * N / math::size(nu);
113 }
115 logp -= sum(log(sigma_val)) * N / math::size(sigma);
116 }
117
118 if constexpr (is_any_autodiff_v<T_y, T_loc>) {
119 const auto& square_sigma = square(sigma_val);
120 auto deriv_y_mu = to_ref_if<(is_autodiff_v<T_y> && is_autodiff_v<T_loc>)>(
121 (nu_val + 1) * (y_val - mu_val)
122 / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
123 if constexpr (is_autodiff_v<T_y>) {
124 partials<0>(ops_partials) = -deriv_y_mu;
125 }
126 if constexpr (is_autodiff_v<T_loc>) {
127 partials<2>(ops_partials) = std::move(deriv_y_mu);
128 }
129 }
130 if constexpr (is_any_autodiff_v<T_dof, T_scale>) {
131 const auto& rep_deriv
132 = to_ref_if<(is_autodiff_v<T_dof> && is_autodiff_v<T_scale>)>(
133 (nu_val + 1) * square_y_scaled_over_nu
134 / (1 + square_y_scaled_over_nu)
135 - 1);
136 if constexpr (is_autodiff_v<T_dof>) {
137 const auto& digamma_half_nu_plus_half = digamma(half_nu + 0.5);
138 const auto& digamma_half_nu = digamma(half_nu);
139 edge<1>(ops_partials).partials_
140 = 0.5
141 * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val
142 + rep_deriv / nu_val);
143 }
144 if constexpr (is_autodiff_v<T_scale>) {
145 partials<3>(ops_partials) = rep_deriv / sigma_val;
146 }
147 }
148 return ops_partials.build(logp);
149}
150
151template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
153 const T_y& y, const T_dof& nu, const T_loc& mu, const T_scale& sigma) {
154 return student_t_lpdf<false>(y, nu, mu, sigma);
155}
156
157} // namespace math
158} // namespace stan
159#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_dof_cl, T_loc_cl, T_scale_cl > student_t_lpdf(const T_y_cl &y, const T_dof_cl &nu, const T_loc_cl &mu, const T_scale_cl &sigma)
The log of the Student-t density for the given y, nu, mean, and scale parameter.
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:45
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.
static constexpr double LOG_SQRT_PI
The natural logarithm of the square root of , .
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.
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
Definition lgamma.hpp:21
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
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:18
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
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 > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
Definition digamma.hpp:23
fvar< T > square(const fvar< T > &x)
Definition square.hpp:12
typename ref_type_if< is_autodiff_v< T >, T >::type ref_type_if_not_constant_t
Definition ref_type.hpp:63
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 ...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...