1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_LOG_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_LOG_HPP
16 #include <boost/random/uniform_01.hpp>
17 #include <boost/random/variate_generator.hpp>
24 template <
typename T_y,
typename T_loc,
typename T_scale>
25 typename return_type<T_y, T_loc, T_scale>::type
27 const T_scale& sigma) {
28 static const char*
function(
"stan::math::double_exponential_cdf_log");
38 T_partials_return cdf_log(0.0);
51 "Location parameter", mu,
52 "Scale Parameter", sigma);
60 operands_and_partials(y, mu, sigma);
65 const double log_half =
std::log(0.5);
68 for (
size_t n = 0; n < N; n++) {
69 const T_partials_return y_dbl =
value_of(y_vec[n]);
70 const T_partials_return mu_dbl =
value_of(mu_vec[n]);
71 const T_partials_return sigma_dbl =
value_of(sigma_vec[n]);
72 const T_partials_return scaled_diff = (y_dbl - mu_dbl) / sigma_dbl;
73 const T_partials_return inv_sigma = 1.0 / sigma_dbl;
76 cdf_log += log_half + scaled_diff;
80 operands_and_partials.
d_x1[n] += inv_sigma;
82 operands_and_partials.
d_x2[n] -= inv_sigma;
84 operands_and_partials.
d_x3[n] -= scaled_diff * inv_sigma;
87 cdf_log +=
log1m(0.5 *
exp(-scaled_diff));
90 const T_partials_return rep_deriv = 1.0
91 / (2.0 *
exp(scaled_diff) - 1.0);
93 operands_and_partials.
d_x1[n] += rep_deriv * inv_sigma;
95 operands_and_partials.
d_x2[n] -= rep_deriv * inv_sigma;
97 operands_and_partials.
d_x3[n] -= rep_deriv * scaled_diff
101 return operands_and_partials.
value(cdf_log);
VectorView< T_return_type, false, true > d_x2
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
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)
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
fvar< T > exp(const fvar< T > &x)
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)
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
return_type< T_y, T_loc, T_scale >::type double_exponential_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
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[].
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
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
fvar< T > log1m(const fvar< T > &x)
VectorView< T_return_type, false, true > d_x1