Automatic Differentiation
 
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chi_square_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_CHI_SQUARE_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_CHI_SQUARE_LPDF_HPP
3
18#include <cmath>
19
20namespace stan {
21namespace math {
22
43template <bool propto, typename T_y, typename T_dof,
45 T_y, T_dof>* = nullptr>
46return_type_t<T_y, T_dof> chi_square_lpdf(const T_y& y, const T_dof& nu) {
47 using T_partials_return = partials_return_t<T_y, T_dof>;
48 using T_partials_array = Eigen::Array<T_partials_return, Eigen::Dynamic, 1>;
49 using std::log;
50 static constexpr const char* function = "chi_square_lpdf";
51 using T_y_ref = ref_type_t<T_y>;
52 using T_nu_ref = ref_type_t<T_dof>;
53 check_consistent_sizes(function, "Random variable", y,
54 "Degrees of freedom parameter", nu);
55 T_y_ref y_ref = y;
56 T_nu_ref nu_ref = nu;
57
58 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
59 decltype(auto) nu_val = to_ref(as_value_column_array_or_scalar(nu_ref));
60
61 check_nonnegative(function, "Random variable", y_val);
62 check_positive_finite(function, "Degrees of freedom parameter", nu_val);
63
64 if (size_zero(y, nu)) {
65 return 0;
66 }
68 return 0;
69 }
70
71 size_t N = max_size(y, nu);
72 const auto& log_y = to_ref_if<!is_constant_all<T_dof>::value>(log(y_val));
73 const auto& half_nu = to_ref(0.5 * nu_val);
74
75 T_partials_return logp(0);
77 logp -= sum(nu_val * HALF_LOG_TWO + lgamma(half_nu)) * N / math::size(nu);
78 }
79 logp += sum((half_nu - 1.0) * log_y);
80
82 logp -= 0.5 * sum(y_val) * N / math::size(y);
83 }
84
85 auto ops_partials = make_partials_propagator(y_ref, nu_ref);
87 partials<0>(ops_partials) = (half_nu - 1.0) / y_val - 0.5;
88 }
91 partials<1>(ops_partials) = forward_as<T_partials_array>(
92 (log_y - digamma(half_nu)) * 0.5 - HALF_LOG_TWO);
93 } else {
94 partials<1>(ops_partials)[0]
95 = sum(log_y - digamma(half_nu)) * 0.5 - HALF_LOG_TWO * N;
96 }
97 }
98 return ops_partials.build(logp);
99}
100
101template <typename T_y, typename T_dof>
103 const T_dof& nu) {
104 return chi_square_lpdf<false>(y, nu);
105}
106
107} // namespace math
108} // namespace stan
109#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 > chi_square_lpdf(const T_y_cl &y, const T_dof_cl &nu)
The log of a 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 HALF_LOG_TWO
The value of half the natural logarithm 2, .
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
fvar< T > log(const fvar< T > &x)
Definition log.hpp:15
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
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
typename ref_type_if< true, T >::type ref_type_t
Definition ref_type.hpp:55
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...