Automatic Differentiation
 
Loading...
Searching...
No Matches
student_t_lpdf.hpp
Go to the documentation of this file.
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_dof& nu,
61 const T_loc& mu,
62 const T_scale& sigma) {
63 using T_partials_return = partials_return_t<T_y, T_dof, T_loc, T_scale>;
64 using T_y_ref = ref_type_if_not_constant_t<T_y>;
65 using T_nu_ref = ref_type_if_not_constant_t<T_dof>;
66 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
67 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
68 static constexpr const char* function = "student_t_lpdf";
69 check_consistent_sizes(function, "Random variable", y,
70 "Degrees of freedom parameter", nu,
71 "Location parameter", mu, "Scale parameter", sigma);
72 T_y_ref y_ref = y;
73 T_mu_ref mu_ref = mu;
74 T_nu_ref nu_ref = nu;
75 T_sigma_ref sigma_ref = sigma;
76
77 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
78 decltype(auto) nu_val = to_ref(as_value_column_array_or_scalar(nu_ref));
79 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
80 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
81
82 check_not_nan(function, "Random variable", y_val);
83 check_positive_finite(function, "Degrees of freedom parameter", nu_val);
84 check_finite(function, "Location parameter", mu_val);
85 check_positive_finite(function, "Scale parameter", sigma_val);
86
87 if (size_zero(y, nu, mu, sigma)) {
88 return 0.0;
89 }
91 return 0.0;
92 }
93
94 auto ops_partials
95 = make_partials_propagator(y_ref, nu_ref, mu_ref, sigma_ref);
96
97 const auto& half_nu
98 = to_ref_if<include_summand<propto, T_dof>::value>(0.5 * nu_val);
99 const auto& square_y_scaled = square((y_val - mu_val) / sigma_val);
100 const auto& square_y_scaled_over_nu
101 = to_ref_if<!is_constant_all<T_y, T_dof, T_loc, T_scale>::value>(
102 square_y_scaled / nu_val);
103 const auto& log1p_val = to_ref_if<!is_constant_all<T_dof>::value>(
104 log1p(square_y_scaled_over_nu));
105
106 size_t N = max_size(y, nu, mu, sigma);
107 T_partials_return logp = -sum((half_nu + 0.5) * log1p_val);
109 logp -= LOG_SQRT_PI * N;
110 }
112 logp += (sum(lgamma(half_nu + 0.5)) - sum(lgamma(half_nu))
113 - 0.5 * sum(log(nu_val)))
114 * N / math::size(nu);
115 }
117 logp -= sum(log(sigma_val)) * N / math::size(sigma);
118 }
119
121 const auto& square_sigma = square(sigma_val);
122 auto deriv_y_mu = to_ref_if<(!is_constant_all<T_y>::value
124 (nu_val + 1) * (y_val - mu_val)
125 / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
127 partials<0>(ops_partials) = -deriv_y_mu;
128 }
130 partials<2>(ops_partials) = std::move(deriv_y_mu);
131 }
132 }
134 const auto& rep_deriv = to_ref_if<(!is_constant_all<T_dof>::value
136 (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu)
137 - 1);
139 const auto& digamma_half_nu_plus_half = digamma(half_nu + 0.5);
140 const auto& digamma_half_nu = digamma(half_nu);
141 edge<1>(ops_partials).partials_
142 = 0.5
143 * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val
144 + rep_deriv / nu_val);
145 }
147 partials<3>(ops_partials) = rep_deriv / sigma_val;
148 }
149 }
150 return ops_partials.build(logp);
151}
152
153template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
155 const T_y& y, const T_dof& nu, const T_loc& mu, const T_scale& sigma) {
156 return student_t_lpdf<false>(y, nu, mu, sigma);
157}
158
159} // namespace math
160} // namespace stan
161#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: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.
static constexpr double LOG_SQRT_PI
The natural logarithm of the square root of , .
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
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
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_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...