Stan Math Library  2.20.0
reverse mode automatic differentiation
exponential_lpdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LPDF_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LPDF_HPP
3 
11 #include <cmath>
12 
13 namespace stan {
14 namespace math {
15 
42 template <bool propto, typename T_y, typename T_inv_scale>
44  const T_y& y, const T_inv_scale& beta) {
45  static const char* function = "exponential_lpdf";
47  T_partials_return;
48 
49  if (size_zero(y, beta))
50  return 0.0;
51 
52  using std::log;
53 
54  T_partials_return logp(0.0);
55  check_nonnegative(function, "Random variable", y);
56  check_positive_finite(function, "Inverse scale parameter", beta);
57  check_consistent_sizes(function, "Random variable", y,
58  "Inverse scale parameter", beta);
59 
60  scalar_seq_view<T_y> y_vec(y);
61  scalar_seq_view<T_inv_scale> beta_vec(beta);
62  size_t N = max_size(y, beta);
63 
65  T_inv_scale>
66  log_beta(length(beta));
67  for (size_t i = 0; i < length(beta); i++)
69  log_beta[i] = log(value_of(beta_vec[i]));
70 
71  operands_and_partials<T_y, T_inv_scale> ops_partials(y, beta);
72 
73  for (size_t n = 0; n < N; n++) {
74  const T_partials_return beta_dbl = value_of(beta_vec[n]);
75  const T_partials_return y_dbl = value_of(y_vec[n]);
77  logp += log_beta[n];
79  logp -= beta_dbl * y_dbl;
80 
82  ops_partials.edge1_.partials_[n] -= beta_dbl;
84  ops_partials.edge2_.partials_[n] += 1 / beta_dbl - y_dbl;
85  }
86  return ops_partials.build(logp);
87 }
88 
89 template <typename T_y, typename T_inv_scale>
91  const T_y& y, const T_inv_scale& beta) {
92  return exponential_lpdf<false>(y, beta);
93 }
94 
95 } // namespace math
96 } // namespace stan
97 #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
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:12
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.
size_t length(const std::vector< T > &x)
Returns the length of the provided std::vector.
Definition: length.hpp:16
bool size_zero(T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
Definition: size_zero.hpp:18
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
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.
return_type< T_y, T_inv_scale >::type exponential_lpdf(const T_y &y, const T_inv_scale &beta)
The log of an exponential density for y with the specified inverse scale parameter.
boost::math::tools::promote_args< double, typename scalar_type< T >::type, typename return_type< Types_pack... >::type >::type type
Definition: return_type.hpp:36
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.
VectorBuilder allocates type T1 values to be used as intermediate values.
internal::ops_partials_edge< double, Op2 > edge2_
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.
internal::ops_partials_edge< double, Op1 > edge1_

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