Stan Math Library  2.12.0
reverse mode automatic differentiation
exp_mod_normal_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_LOG_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_LOG_HPP
3 
14 #include <boost/random/normal_distribution.hpp>
15 #include <boost/random/variate_generator.hpp>
16 #include <cmath>
17 
18 namespace stan {
19  namespace math {
20 
21  template <bool propto,
22  typename T_y, typename T_loc, typename T_scale,
23  typename T_inv_scale>
24  typename return_type<T_y, T_loc, T_scale, T_inv_scale>::type
25  exp_mod_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
26  const T_inv_scale& lambda) {
27  static const char* function("exp_mod_normal_log");
28  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
29  T_inv_scale>::type
30  T_partials_return;
31 
33  using std::log;
34 
35  if (!(stan::length(y)
36  && stan::length(mu)
37  && stan::length(sigma)
38  && stan::length(lambda)))
39  return 0.0;
40 
41  T_partials_return logp(0.0);
42 
43  check_not_nan(function, "Random variable", y);
44  check_finite(function, "Location parameter", mu);
45  check_positive_finite(function, "Inv_scale parameter", lambda);
46  check_positive_finite(function, "Scale parameter", sigma);
47  check_consistent_sizes(function,
48  "Random variable", y,
49  "Location parameter", mu,
50  "Scale parameter", sigma,
51  "Inv_scale paramter", lambda);
52 
54  return 0.0;
55 
56  using boost::math::erfc;
57  using std::sqrt;
58  using std::log;
59  using std::exp;
60 
62  operands_and_partials(y, mu, sigma, lambda);
63 
64  VectorView<const T_y> y_vec(y);
65  VectorView<const T_loc> mu_vec(mu);
66  VectorView<const T_scale> sigma_vec(sigma);
67  VectorView<const T_inv_scale> lambda_vec(lambda);
68  size_t N = max_size(y, mu, sigma, lambda);
69 
70  for (size_t n = 0; n < N; n++) {
71  const T_partials_return y_dbl = value_of(y_vec[n]);
72  const T_partials_return mu_dbl = value_of(mu_vec[n]);
73  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
74  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
75 
76  const T_partials_return pi_dbl = boost::math::constants::pi<double>();
77 
79  logp -= log(2.0);
81  logp += log(lambda_dbl);
83  logp += lambda_dbl
84  * (mu_dbl + 0.5 * lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
85  + log(erfc((mu_dbl + lambda_dbl * sigma_dbl
86  * sigma_dbl - y_dbl)
87  / (sqrt(2.0) * sigma_dbl)));
88 
89  const T_partials_return deriv_logerfc
90  = -2.0 / sqrt(pi_dbl)
91  * exp(-(mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
92  / (std::sqrt(2.0) * sigma_dbl)
93  * (mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
94  / (sigma_dbl * std::sqrt(2.0)))
95  / erfc((mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl
96  - y_dbl) / (sigma_dbl * std::sqrt(2.0)));
97 
99  operands_and_partials.d_x1[n]
100  += -lambda_dbl
101  + deriv_logerfc * -1.0 / (sigma_dbl * std::sqrt(2.0));
103  operands_and_partials.d_x2[n]
104  += lambda_dbl
105  + deriv_logerfc / (sigma_dbl * std::sqrt(2.0));
107  operands_and_partials.d_x3[n]
108  += sigma_dbl * lambda_dbl * lambda_dbl
109  + deriv_logerfc
110  * (-mu_dbl / (sigma_dbl * sigma_dbl * std::sqrt(2.0))
111  + lambda_dbl / std::sqrt(2.0)
112  + y_dbl / (sigma_dbl * sigma_dbl * std::sqrt(2.0)));
114  operands_and_partials.d_x4[n]
115  += 1 / lambda_dbl + lambda_dbl * sigma_dbl * sigma_dbl
116  + mu_dbl - y_dbl + deriv_logerfc * sigma_dbl / std::sqrt(2.0);
117  }
118  return operands_and_partials.value(logp);
119  }
120 
121  template <typename T_y, typename T_loc, typename T_scale,
122  typename T_inv_scale>
123  inline
125  exp_mod_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
126  const T_inv_scale& lambda) {
127  return exp_mod_normal_log<false>(y, mu, sigma, lambda);
128  }
129 
130  }
131 }
132 #endif
133 
VectorView< T_return_type, false, true > d_x2
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:14
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:14
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
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
This class builds partial derivatives with respect to a set of operands.
VectorView< T_return_type, false, true > d_x3
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.
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.
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
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
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
VectorView< T_return_type, false, true > d_x4

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