Automatic Differentiation
 
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beta_proportion_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_BETA_PROPORTION_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_BETA_PROPORTION_LPDF_HPP
3
21#include <cmath>
22
23namespace stan {
24namespace math {
25
48template <bool propto, typename T_y, typename T_loc, typename T_prec,
50 T_y, T_loc, T_prec>* = nullptr>
52 const T_y& y, const T_loc& mu, const T_prec& kappa) {
53 using T_partials_return = partials_return_t<T_y, T_loc, T_prec>;
54 using std::log;
55 using T_y_ref = ref_type_if_not_constant_t<T_y>;
56 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
57 using T_kappa_ref = ref_type_if_not_constant_t<T_prec>;
58 static constexpr const char* function = "beta_proportion_lpdf";
59 check_consistent_sizes(function, "Random variable", y, "Location parameter",
60 mu, "Precision parameter", kappa);
61 if (size_zero(y, mu, kappa)) {
62 return 0;
63 }
64
65 T_y_ref y_ref = y;
66 T_mu_ref mu_ref = mu;
67 T_kappa_ref kappa_ref = kappa;
68
69 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
70 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
71 decltype(auto) kappa_val = to_ref(as_value_column_array_or_scalar(kappa_ref));
72
73 check_positive(function, "Location parameter", mu_val);
74 check_less(function, "Location parameter", mu_val, 1.0);
75 check_positive_finite(function, "Precision parameter", kappa_val);
76 check_bounded(function, "Random variable", value_of(y_val), 0, 1);
77
79 return 0;
80 }
81
82 const auto& log_y = to_ref_if<is_any_autodiff_v<T_loc, T_prec>>(log(y_val));
83 const auto& log1m_y
84 = to_ref_if<is_any_autodiff_v<T_loc, T_prec>>(log1m(y_val));
85 const auto& mukappa = to_ref(mu_val * kappa_val);
86
87 size_t N = max_size(y, mu, kappa);
88 T_partials_return logp(0);
90 logp += sum(lgamma(kappa_val)) * N / math::size(kappa);
91 }
93 logp -= sum(lgamma(mukappa) + lgamma(kappa_val - mukappa)) * N
94 / max_size(mu, kappa_val);
95 }
96 logp += sum((mukappa - 1) * log_y + (kappa_val - mukappa - 1) * log1m_y);
97
98 auto ops_partials = make_partials_propagator(y_ref, mu_ref, kappa_ref);
99 if constexpr (is_autodiff_v<T_y>) {
100 edge<0>(ops_partials).partials_
101 = (mukappa - 1) / y_val + (kappa_val - mukappa - 1) / (y_val - 1);
102 }
103 if constexpr (is_any_autodiff_v<T_loc, T_prec>) {
104 auto digamma_mukappa
105 = to_ref_if<(is_autodiff_v<T_loc> && is_autodiff_v<T_prec>)>(
106 digamma(mukappa));
107 auto digamma_kappa_mukappa
108 = to_ref_if<(is_autodiff_v<T_loc> && is_autodiff_v<T_prec>)>(
109 digamma(kappa_val - mukappa));
110 if constexpr (is_autodiff_v<T_loc>) {
111 edge<1>(ops_partials).partials_
112 = kappa_val
113 * (digamma_kappa_mukappa - digamma_mukappa + log_y - log1m_y);
114 }
115 if constexpr (is_autodiff_v<T_prec>) {
116 edge<2>(ops_partials).partials_
117 = digamma(kappa_val) + mu_val * (log_y - digamma_mukappa)
118 + (1 - mu_val) * (log1m_y - digamma_kappa_mukappa);
119 }
120 }
121 return ops_partials.build(logp);
122}
123
124template <typename T_y, typename T_loc, typename T_prec>
126 const T_y& y, const T_loc& mu, const T_prec& kappa) {
127 return beta_proportion_lpdf<false>(y, mu, kappa);
128}
129
130} // namespace math
131} // namespace stan
132#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_prec_cl > beta_proportion_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_prec_cl &kappa)
The log of the beta density for specified y, location, and precision: beta_proportion_lpdf(y | mu,...
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
void check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Check if the value is between the low and high values, inclusively.
T to_ref_if(T &&a)
No-op that should be optimized away.
Definition to_ref.hpp:45
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition value_of.hpp:18
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.
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
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:18
void check_less(const char *function, const char *name, const T_y &y, const T_high &high, Idxs... idxs)
Throw an exception if y is not strictly less than high.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
fvar< T > log1m(const fvar< T > &x)
Definition log1m.hpp:12
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_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...