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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 
4 #include <boost/random/uniform_01.hpp>
5 #include <boost/random/variate_generator.hpp>
18 #include <cmath>
19 
20 namespace stan {
21 
22  namespace math {
23 
24  // DoubleExponential(y|mu, sigma) [sigma > 0]
25  // FIXME: add documentation
26  template <bool propto,
27  typename T_y, typename T_loc, typename T_scale>
28  typename return_type<T_y, T_loc, T_scale>::type
29  double_exponential_log(const T_y& y,
30  const T_loc& mu, const T_scale& sigma) {
31  static const char* function("stan::math::double_exponential_log");
33  T_partials_return;
34 
41  using std::log;
42  using std::fabs;
43  using stan::math::sign;
44  using std::log;
45 
46  // check if any vectors are zero length
47  if (!(stan::length(y)
48  && stan::length(mu)
49  && stan::length(sigma)))
50  return 0.0;
51 
52  // set up return value accumulator
53  T_partials_return logp(0.0);
54  check_finite(function, "Random variable", y);
55  check_finite(function, "Location parameter", mu);
56  check_positive_finite(function, "Scale parameter", sigma);
57  check_consistent_sizes(function,
58  "Random variable", y,
59  "Location parameter", mu,
60  "Shape parameter", sigma);
61 
62  // check if no variables are involved and prop-to
64  return 0.0;
65 
66  // set up template expressions wrapping scalars into vector views
67  VectorView<const T_y> y_vec(y);
68  VectorView<const T_loc> mu_vec(mu);
69  VectorView<const T_scale> sigma_vec(sigma);
70  size_t N = max_size(y, mu, sigma);
72  operands_and_partials(y, mu, sigma);
73 
75  T_partials_return, T_scale> inv_sigma(length(sigma));
77  T_partials_return, T_scale>
78  inv_sigma_squared(length(sigma));
80  T_partials_return, T_scale> log_sigma(length(sigma));
81  for (size_t i = 0; i < length(sigma); i++) {
82  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
84  inv_sigma[i] = 1.0 / sigma_dbl;
86  log_sigma[i] = log(value_of(sigma_vec[i]));
88  inv_sigma_squared[i] = inv_sigma[i] * inv_sigma[i];
89  }
90 
91 
92  for (size_t n = 0; n < N; n++) {
93  const T_partials_return y_dbl = value_of(y_vec[n]);
94  const T_partials_return mu_dbl = value_of(mu_vec[n]);
95 
96  // reusable subexpressions values
97  const T_partials_return y_m_mu = y_dbl - mu_dbl;
98  const T_partials_return fabs_y_m_mu = fabs(y_m_mu);
99 
100  // log probability
102  logp += NEG_LOG_TWO;
104  logp -= log_sigma[n];
106  logp -= fabs_y_m_mu * inv_sigma[n];
107 
108  // gradients
109  T_partials_return sign_y_m_mu_times_inv_sigma(0);
111  sign_y_m_mu_times_inv_sigma = sign(y_m_mu) * inv_sigma[n];
113  operands_and_partials.d_x1[n] -= sign_y_m_mu_times_inv_sigma;
114  }
116  operands_and_partials.d_x2[n] += sign_y_m_mu_times_inv_sigma;
117  }
119  operands_and_partials.d_x3[n] += -inv_sigma[n] + fabs_y_m_mu
120  * inv_sigma_squared[n];
121  }
122  return operands_and_partials.to_var(logp, y, mu, sigma);
123  }
124 
125 
126  template <typename T_y, typename T_loc, typename T_scale>
128  double_exponential_log(const T_y& y, const T_loc& mu,
129  const T_scale& sigma) {
130  return double_exponential_log<false>(y, mu, sigma);
131  }
132  }
133 }
134 #endif
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
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
T_return_type to_var(T_partials_return logp, const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
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
VectorView< T_partials_return, is_vector< T1 >::value, is_constant_struct< T1 >::value > d_x1
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
VectorView< T_partials_return, is_vector< T3 >::value, is_constant_struct< T3 >::value > d_x3
A variable implementation that stores operands and derivatives with respect to the variable...
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
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< T_partials_return, is_vector< T2 >::value, is_constant_struct< T2 >::value > d_x2
VectorView is a template metaprogram that takes its argument and allows it to be used like a vector...
Definition: VectorView.hpp:41
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.

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