Automatic Differentiation
 
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normal_lpdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_NORMAL_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_NORMAL_LPDF_HPP
3
17#include <cmath>
18
19namespace stan {
20namespace math {
21
41template <bool propto, typename T_y, typename T_loc, typename T_scale,
43 T_y, T_loc, T_scale>* = nullptr>
45 const T_loc& mu,
46 const T_scale& sigma) {
47 using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
48 using T_y_ref = ref_type_if_not_constant_t<T_y>;
49 using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
50 using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
51 static constexpr const char* function = "normal_lpdf";
52 check_consistent_sizes(function, "Random variable", y, "Location parameter",
53 mu, "Scale parameter", sigma);
54 T_y_ref y_ref = y;
55 T_mu_ref mu_ref = mu;
56 T_sigma_ref sigma_ref = sigma;
57
58 decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
59 decltype(auto) mu_val = to_ref(as_value_column_array_or_scalar(mu_ref));
60 decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
61
62 check_not_nan(function, "Random variable", y_val);
63 check_finite(function, "Location parameter", mu_val);
64 check_positive(function, "Scale parameter", sigma_val);
65
66 if (size_zero(y, mu, sigma)) {
67 return 0.0;
68 }
70 return 0.0;
71 }
72
73 auto ops_partials = make_partials_propagator(y_ref, mu_ref, sigma_ref);
74
75 const auto& inv_sigma
76 = to_ref_if<!is_constant_all<T_y, T_scale, T_loc>::value>(inv(sigma_val));
77 const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma);
78 const auto& y_scaled_sq
79 = to_ref_if<!is_constant_all<T_scale>::value>(y_scaled * y_scaled);
80
81 size_t N = max_size(y, mu, sigma);
82 T_partials_return logp = -0.5 * sum(y_scaled_sq);
84 logp += NEG_LOG_SQRT_TWO_PI * N;
85 }
87 logp -= sum(log(sigma_val)) * N / math::size(sigma);
88 }
89
91 auto scaled_diff = to_ref_if<!is_constant_all<T_y>::value
94 >= 2>(inv_sigma * y_scaled);
96 partials<0>(ops_partials) = -scaled_diff;
97 }
99 partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
100 }
102 partials<1>(ops_partials) = std::move(scaled_diff);
103 }
104 }
105 return ops_partials.build(logp);
106}
107
108template <typename T_y, typename T_loc, typename T_scale>
110 const T_loc& mu,
111 const T_scale& sigma) {
112 return normal_lpdf<false>(y, mu, sigma);
113}
114
115} // namespace math
116} // namespace stan
117#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 > normal_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s...
size_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:18
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
size_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_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
fvar< T > log(const fvar< T > &x)
Definition log.hpp:15
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.
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:22
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
void check_finite(const char *function, const char *name, const T_y &y)
Return true if all values in y are finite.
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
fvar< T > inv(const fvar< T > &x)
Definition inv.hpp:12
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
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 ...
Definition fvar.hpp:9
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...