Stan Math Library  2.20.0
reverse mode automatic differentiation
exponential_lccdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LCCDF_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LCCDF_HPP
3 
10 
11 namespace stan {
12 namespace math {
13 
14 template <typename T_y, typename T_inv_scale>
16  const T_y& y, const T_inv_scale& beta) {
18  T_partials_return;
19 
20  static const char* function = "exponential_lccdf";
21 
22  T_partials_return ccdf_log(0.0);
23  if (size_zero(y, beta))
24  return ccdf_log;
25 
26  check_not_nan(function, "Random variable", y);
27  check_nonnegative(function, "Random variable", y);
28  check_positive_finite(function, "Inverse scale parameter", beta);
29 
30  operands_and_partials<T_y, T_inv_scale> ops_partials(y, beta);
31 
32  scalar_seq_view<T_y> y_vec(y);
33  scalar_seq_view<T_inv_scale> beta_vec(beta);
34  size_t N = max_size(y, beta);
35  for (size_t n = 0; n < N; n++) {
36  const T_partials_return beta_dbl = value_of(beta_vec[n]);
37  const T_partials_return y_dbl = value_of(y_vec[n]);
38  ccdf_log += -beta_dbl * y_dbl;
39 
41  ops_partials.edge1_.partials_[n] -= beta_dbl;
43  ops_partials.edge2_.partials_[n] -= y_dbl;
44  }
45  return ops_partials.build(ccdf_log);
46 }
47 
48 } // namespace math
49 } // namespace stan
50 #endif
boost::math::tools::promote_args< double, typename partials_type< typename scalar_type< T >::type >::type, typename partials_return_type< T_pack... >::type >::type type
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:17
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...
Definition: conjunction.hpp:14
scalar_seq_view provides a uniform sequence-like wrapper around either a scalar or a sequence of scal...
This template builds partial derivatives with respect to a set of operands.
bool size_zero(T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition: size_zero.hpp:18
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
fvar< T > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
Definition: beta.hpp:51
void check_positive_finite(const char *function, const char *name, const T_y &y)
Check if y is positive and finite.
boost::math::tools::promote_args< double, typename scalar_type< T >::type, typename return_type< Types_pack... >::type >::type type
Definition: return_type.hpp:36
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
T_return_type build(double value)
Build the node to be stored on the autodiff graph.
internal::ops_partials_edge< double, Op2 > edge2_
internal::ops_partials_edge< double, Op1 > edge1_
return_type< T_y, T_inv_scale >::type exponential_lccdf(const T_y &y, const T_inv_scale &beta)

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