Automatic Differentiation
 
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lognormal_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_LOGNORMAL_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_LOGNORMAL_LPDF_HPP
3
19#include <cmath>
20
21namespace stan {
22namespace math {
23
24// LogNormal(y|mu, sigma) [y >= 0; sigma > 0]
25template <bool propto, typename T_y, typename T_loc, typename T_scale,
27 T_y, T_loc, T_scale>* = nullptr>
29 const T_loc& mu,
30 const T_scale& sigma) {
31 using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
32 using T_y_ref = ref_type_if_not_constant_t<T_y>;
33 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
34 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
35 static constexpr const char* function = "lognormal_lpdf";
36 check_consistent_sizes(function, "Random variable", y, "Location parameter",
37 mu, "Scale parameter", sigma);
38
39 T_y_ref y_ref = y;
40 T_mu_ref mu_ref = mu;
41 T_sigma_ref sigma_ref = sigma;
42
43 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
44 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
45 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
46
47 check_nonnegative(function, "Random variable", y_val);
48 check_finite(function, "Location parameter", mu_val);
49 check_positive_finite(function, "Scale parameter", sigma_val);
50
51 if (size_zero(y, mu, sigma)) {
52 return 0;
53 }
55 return 0;
56 }
57
58 auto ops_partials = make_partials_propagator(y_ref, mu_ref, sigma_ref);
59
60 if (sum(promote_scalar<int>(y_val == 0))) {
61 return ops_partials.build(LOG_ZERO);
62 }
63
64 const auto& inv_sigma = to_ref_if<is_autodiff_v<T_scale>>(inv(sigma_val));
65 const auto& inv_sigma_sq
66 = to_ref_if<is_any_autodiff_v<T_y, T_loc, T_scale>>(square(inv_sigma));
67 const auto& log_y
68 = to_ref_if<include_summand<propto, T_y>::value>(log(y_val));
69 const auto& logy_m_mu = to_ref(log_y - mu_val);
70
71 size_t N = max_size(y, mu, sigma);
72 T_partials_return logp
73 = N * NEG_LOG_SQRT_TWO_PI - 0.5 * sum(square(logy_m_mu) * inv_sigma_sq);
75 logp -= sum(log(sigma_val)) * N / math::size(sigma);
76 }
78 logp -= sum(log_y) * N / math::size(y);
79 }
80
81 if constexpr (is_any_autodiff_v<T_y, T_loc, T_scale>) {
82 const auto& logy_m_mu_div_sigma = to_ref_if<
84 T_y> + is_autodiff_v<T_loc> + is_autodiff_v<T_scale> >= 2>(
85 logy_m_mu * inv_sigma_sq);
86 if constexpr (is_autodiff_v<T_y>) {
87 partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val;
88 }
89 if constexpr (is_autodiff_v<T_loc>) {
90 partials<1>(ops_partials) = logy_m_mu_div_sigma;
91 }
92 if constexpr (is_autodiff_v<T_scale>) {
93 edge<2>(ops_partials).partials_
94 = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
95 }
96 }
97 return ops_partials.build(logp);
98}
99
100template <typename T_y, typename T_loc, typename T_scale>
102 const T_loc& mu,
103 const T_scale& sigma) {
104 return lognormal_lpdf<false>(y, mu, sigma);
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_loc_cl, T_scale_cl > lognormal_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
The log of the lognormal density for the specified scalar(s) given the specified sample stan::math::s...
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
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
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
const double NEG_LOG_SQRT_TWO_PI
The value of minus the natural logarithm of the square root of , .
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.
void check_finite(const char *function, const char *name, const T_y &y)
Return true if all values in y are finite.
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
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 > 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
constexpr bool is_autodiff_v
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...