Automatic Differentiation
 
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inv_chi_square_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_INV_CHI_SQUARE_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_INV_CHI_SQUARE_LPDF_HPP
3
21#include <cmath>
22
23namespace stan {
24namespace math {
25
46template <bool propto, typename T_y, typename T_dof,
48 T_y, T_dof>* = nullptr>
49return_type_t<T_y, T_dof> inv_chi_square_lpdf(const T_y& y, const T_dof& nu) {
50 using T_partials_return = partials_return_t<T_y, T_dof>;
51 using T_y_ref = ref_type_if_not_constant_t<T_y>;
52 using T_nu_ref = ref_type_if_not_constant_t<T_dof>;
53 static constexpr const char* function = "inv_chi_square_lpdf";
54 check_consistent_sizes(function, "Random variable", y,
55 "Degrees of freedom parameter", nu);
56
57 T_y_ref y_ref = y;
58 T_nu_ref nu_ref = nu;
59
60 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
61 decltype(auto) nu_val = to_ref(as_value_column_array_or_scalar(nu_ref));
62
63 check_positive_finite(function, "Degrees of freedom parameter", nu_val);
64 check_not_nan(function, "Random variable", y_val);
65
66 if (size_zero(y, nu)) {
67 return 0;
68 }
70 return 0;
71 }
72
73 if (sum(promote_scalar<int>(y_val <= 0))) {
74 return LOG_ZERO;
75 }
76
77 auto ops_partials = make_partials_propagator(y_ref, nu_ref);
78
79 const auto& log_y = to_ref_if<!is_constant_all<T_dof>::value>(log(y_val));
80 const auto& half_nu = to_ref(0.5 * nu_val);
81
82 size_t N = max_size(y, nu);
83 T_partials_return logp = -sum((half_nu + 1.0) * log_y);
85 logp -= (sum(nu_val) * HALF_LOG_TWO + sum(lgamma(half_nu))) * N
86 / math::size(nu);
87 }
89 const auto& inv_y = to_ref_if<!is_constant_all<T_y>::value>(inv(y_val));
90 logp -= 0.5 * sum(inv_y) * N / math::size(y);
92 partials<0>(ops_partials) = (0.5 * inv_y - half_nu - 1.0) * inv_y;
93 }
94 }
95
97 edge<1>(ops_partials).partials_
98 = -HALF_LOG_TWO - (digamma(half_nu) + log_y) * 0.5;
99 }
100 return ops_partials.build(logp);
101}
102
103template <typename T_y, typename T_dof>
105 const T_dof& nu) {
106 return inv_chi_square_lpdf<false>(y, nu);
107}
108
109} // namespace math
110} // namespace stan
111#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 > inv_chi_square_lpdf(const T_y_cl &y, const T_dof_cl &nu)
The log of an inverse chi-squared density for y with the specified degrees of freedom 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
static constexpr double LOG_ZERO
The natural logarithm of 0, .
Definition constants.hpp:68
static constexpr double HALF_LOG_TWO
The value of half the natural logarithm 2, .
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition size_zero.hpp:19
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
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
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 > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
Definition digamma.hpp:23
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...