Stan Math Library  2.10.0
reverse mode automatic differentiation
double_exponential_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LOG_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LOG_HPP
3 
18 #include <boost/random/uniform_01.hpp>
19 #include <boost/random/variate_generator.hpp>
20 #include <cmath>
21 
22 namespace stan {
23 
24  namespace math {
25 
26  // DoubleExponential(y|mu, sigma) [sigma > 0]
27  // FIXME: add documentation
28  template <bool propto,
29  typename T_y, typename T_loc, typename T_scale>
30  typename return_type<T_y, T_loc, T_scale>::type
31  double_exponential_log(const T_y& y,
32  const T_loc& mu, const T_scale& sigma) {
33  static const char* function("stan::math::double_exponential_log");
35  T_partials_return;
36 
43  using std::log;
44  using std::fabs;
45  using stan::math::sign;
46  using std::log;
47 
48  // check if any vectors are zero length
49  if (!(stan::length(y)
50  && stan::length(mu)
51  && stan::length(sigma)))
52  return 0.0;
53 
54  // set up return value accumulator
55  T_partials_return logp(0.0);
56  check_finite(function, "Random variable", y);
57  check_finite(function, "Location parameter", mu);
58  check_positive_finite(function, "Scale parameter", sigma);
59  check_consistent_sizes(function,
60  "Random variable", y,
61  "Location parameter", mu,
62  "Shape parameter", sigma);
63 
64  // check if no variables are involved and prop-to
66  return 0.0;
67 
68  // set up template expressions wrapping scalars into vector views
69  VectorView<const T_y> y_vec(y);
70  VectorView<const T_loc> mu_vec(mu);
71  VectorView<const T_scale> sigma_vec(sigma);
72  size_t N = max_size(y, mu, sigma);
74  operands_and_partials(y, mu, sigma);
75 
77  T_partials_return, T_scale> inv_sigma(length(sigma));
79  T_partials_return, T_scale>
80  inv_sigma_squared(length(sigma));
82  T_partials_return, T_scale> log_sigma(length(sigma));
83  for (size_t i = 0; i < length(sigma); i++) {
84  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
86  inv_sigma[i] = 1.0 / sigma_dbl;
88  log_sigma[i] = log(value_of(sigma_vec[i]));
90  inv_sigma_squared[i] = inv_sigma[i] * inv_sigma[i];
91  }
92 
93 
94  for (size_t n = 0; n < N; n++) {
95  const T_partials_return y_dbl = value_of(y_vec[n]);
96  const T_partials_return mu_dbl = value_of(mu_vec[n]);
97 
98  // reusable subexpressions values
99  const T_partials_return y_m_mu = y_dbl - mu_dbl;
100  const T_partials_return fabs_y_m_mu = fabs(y_m_mu);
101 
102  // log probability
104  logp += NEG_LOG_TWO;
106  logp -= log_sigma[n];
108  logp -= fabs_y_m_mu * inv_sigma[n];
109 
110  // gradients
111  T_partials_return sign_y_m_mu_times_inv_sigma(0);
113  sign_y_m_mu_times_inv_sigma = sign(y_m_mu) * inv_sigma[n];
115  operands_and_partials.d_x1[n] -= sign_y_m_mu_times_inv_sigma;
116  }
118  operands_and_partials.d_x2[n] += sign_y_m_mu_times_inv_sigma;
119  }
121  operands_and_partials.d_x3[n] += -inv_sigma[n] + fabs_y_m_mu
122  * inv_sigma_squared[n];
123  }
124  return operands_and_partials.value(logp);
125  }
126 
127 
128  template <typename T_y, typename T_loc, typename T_scale>
130  double_exponential_log(const T_y& y, const T_loc& mu,
131  const T_scale& sigma) {
132  return double_exponential_log<false>(y, mu, sigma);
133  }
134  }
135 }
136 #endif
VectorView< T_return_type, false, true > d_x2
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
int sign(const T &z)
Definition: sign.hpp:9
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
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)
Definition: length.hpp:10
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
Definition: return_type.hpp:27
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
This class builds partial derivatives with respect to a set of operands.
VectorView< T_return_type, false, true > d_x3
return_type< T_y, T_loc, T_scale >::type double_exponential_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
const double NEG_LOG_TWO
Definition: constants.hpp:181
VectorBuilder allocates type T1 values to be used as intermediate values.
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.
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[].
Definition: VectorView.hpp:48
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.
VectorView< T_return_type, false, true > d_x1

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