Stan Math Library  2.20.0
reverse mode automatic differentiation
double_exponential_lpdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LPDF_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LPDF_HPP
3 
12 #include <cmath>
13 
14 namespace stan {
15 namespace math {
16 
31 template <bool propto, typename T_y, typename T_loc, typename T_scale>
33  const T_y& y, const T_loc& mu, const T_scale& sigma) {
34  static const char* function = "double_exponential_lpdf";
36  T_partials_return;
37 
38  using std::fabs;
39  using std::log;
40 
41  if (size_zero(y, mu, sigma))
42  return 0.0;
43 
44  T_partials_return logp(0.0);
45  check_finite(function, "Random variable", y);
46  check_finite(function, "Location parameter", mu);
47  check_positive_finite(function, "Scale parameter", sigma);
48  check_consistent_sizes(function, "Random variable", y, "Location parameter",
49  mu, "Shape parameter", sigma);
50 
52  return 0.0;
53 
54  scalar_seq_view<T_y> y_vec(y);
55  scalar_seq_view<T_loc> mu_vec(mu);
56  scalar_seq_view<T_scale> sigma_vec(sigma);
57  size_t N = max_size(y, mu, sigma);
58  operands_and_partials<T_y, T_loc, T_scale> ops_partials(y, mu, sigma);
59 
61  T_partials_return, T_scale>
62  inv_sigma(length(sigma));
63  VectorBuilder<!is_constant_all<T_scale>::value, T_partials_return, T_scale>
64  inv_sigma_squared(length(sigma));
66  T_scale>
67  log_sigma(length(sigma));
68  for (size_t i = 0; i < length(sigma); i++) {
69  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
71  inv_sigma[i] = 1.0 / sigma_dbl;
73  log_sigma[i] = log(value_of(sigma_vec[i]));
75  inv_sigma_squared[i] = inv_sigma[i] * inv_sigma[i];
76  }
77 
78  for (size_t n = 0; n < N; n++) {
79  const T_partials_return y_dbl = value_of(y_vec[n]);
80  const T_partials_return mu_dbl = value_of(mu_vec[n]);
81 
82  const T_partials_return y_m_mu = y_dbl - mu_dbl;
83  const T_partials_return fabs_y_m_mu = fabs(y_m_mu);
84 
86  logp += NEG_LOG_TWO;
88  logp -= log_sigma[n];
90  logp -= fabs_y_m_mu * inv_sigma[n];
91 
92  T_partials_return sign_y_m_mu_times_inv_sigma(0);
94  sign_y_m_mu_times_inv_sigma = sign(y_m_mu) * inv_sigma[n];
96  ops_partials.edge1_.partials_[n] -= sign_y_m_mu_times_inv_sigma;
97  }
99  ops_partials.edge2_.partials_[n] += sign_y_m_mu_times_inv_sigma;
100  }
102  ops_partials.edge3_.partials_[n]
103  += -inv_sigma[n] + fabs_y_m_mu * inv_sigma_squared[n];
104  }
105  return ops_partials.build(logp);
106 }
107 
108 template <typename T_y, typename T_loc, typename T_scale>
110  const T_y& y, const T_loc& mu, const T_scale& sigma) {
111  return double_exponential_lpdf<false>(y, mu, sigma);
112 }
113 
114 } // namespace math
115 } // namespace stan
116 #endif
void check_finite(const char *function, const char *name, const T_y &y)
Check if y is finite.
boost::math::tools::promote_args< double, typename partials_type< typename scalar_type< T >::type >::type, typename partials_return_type< T_pack... >::type >::type type
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:15
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
int sign(const T &z)
Definition: sign.hpp:10
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_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
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.
const double NEG_LOG_TWO
Definition: constants.hpp:154
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.
return_type< T_y, T_loc, T_scale >::type double_exponential_lpdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
Returns the double exponential log probability density function.
internal::ops_partials_edge< double, Op3 > edge3_
internal::ops_partials_edge< double, Op1 > edge1_

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