1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_LOG_HPP 2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_LOG_HPP 16 #include <boost/random/normal_distribution.hpp> 17 #include <boost/random/variate_generator.hpp> 41 template <
bool propto,
42 typename T_y,
typename T_loc,
typename T_scale>
44 normal_log(
const T_y& y,
const T_loc& mu,
const T_scale& sigma) {
45 static const char*
function(
"normal_log");
58 T_partials_return logp(0.0);
65 "Location parameter", mu,
66 "Scale parameter", sigma);
71 operands_and_partials(y, mu, sigma);
80 T_partials_return, T_scale> log_sigma(
length(sigma));
81 for (
size_t i = 0; i <
length(sigma); i++) {
82 inv_sigma[i] = 1.0 /
value_of(sigma_vec[i]);
87 for (
size_t n = 0; n < N; n++) {
88 const T_partials_return y_dbl =
value_of(y_vec[n]);
89 const T_partials_return mu_dbl =
value_of(mu_vec[n]);
91 const T_partials_return y_minus_mu_over_sigma
92 = (y_dbl - mu_dbl) * inv_sigma[n];
93 const T_partials_return y_minus_mu_over_sigma_squared
94 = y_minus_mu_over_sigma * y_minus_mu_over_sigma;
96 static double NEGATIVE_HALF = - 0.5;
101 logp -= log_sigma[n];
103 logp += NEGATIVE_HALF * y_minus_mu_over_sigma_squared;
105 T_partials_return scaled_diff = inv_sigma[n] * y_minus_mu_over_sigma;
107 operands_and_partials.
d_x1[n] -= scaled_diff;
109 operands_and_partials.
d_x2[n] += scaled_diff;
111 operands_and_partials.
d_x3[n]
112 += -inv_sigma[n] + inv_sigma[n] * y_minus_mu_over_sigma_squared;
114 return operands_and_partials.
value(logp);
117 template <
typename T_y,
typename T_loc,
typename T_scale>
120 normal_log(
const T_y& y,
const T_loc& mu,
const T_scale& sigma) {
121 return normal_log<false>(y, mu, sigma);
VectorView< T_return_type, false, true > d_x2
void check_finite(const char *function, const char *name, const T_y &y)
Check if y is finite.
T value_of(const fvar< T > &v)
Return the value of the specified variable.
fvar< T > log(const fvar< T > &x)
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
size_t length(const std::vector< T > &x)
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
This class builds partial derivatives with respect to a set of operands.
VectorView< T_return_type, false, true > d_x3
size_t max_size(const T1 &x1, const T2 &x2)
const double NEG_LOG_SQRT_TWO_PI
return_type< T_y, T_loc, T_scale >::type normal_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s...
VectorBuilder allocates type T1 values to be used as intermediate values.
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
void check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Check if the dimension of x1 is consistent with x2.
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
VectorView< T_return_type, false, true > d_x1