Stan Math Library  2.11.0
reverse mode automatic differentiation
multi_normal_log.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LOG_HPP
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LOG_HPP
3 
17 #include <boost/random/normal_distribution.hpp>
18 #include <boost/random/variate_generator.hpp>
19 
20 namespace stan {
21 
22  namespace math {
23 
24  template <bool propto,
25  typename T_y, typename T_loc, typename T_covar>
26  typename return_type<T_y, T_loc, T_covar>::type
27  multi_normal_log(const T_y& y,
28  const T_loc& mu,
29  const T_covar& Sigma) {
30  static const char* function("stan::math::multi_normal_log");
31  typedef typename scalar_type<T_covar>::type T_covar_elem;
32  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
33  lp_type lp(0.0);
34 
41  using Eigen::Dynamic;
42 
43  check_positive(function, "Covariance matrix rows", Sigma.rows());
44  check_symmetric(function, "Covariance matrix", Sigma);
45 
47  check_ldlt_factor(function,
48  "LDLT_Factor of covariance parameter", ldlt_Sigma);
49 
50  VectorViewMvt<const T_y> y_vec(y);
51  VectorViewMvt<const T_loc> mu_vec(mu);
52  // size of std::vector of Eigen vectors
53  size_t size_vec = max_size_mvt(y, mu);
54 
55  // Check if every vector of the array has the same size
56  int size_y = y_vec[0].size();
57  int size_mu = mu_vec[0].size();
58  if (size_vec > 1) {
59  int size_y_old = size_y;
60  int size_y_new;
61  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
62  int size_y_new = y_vec[i].size();
63  check_size_match(function,
64  "Size of one of the vectors of "
65  "the random variable", size_y_new,
66  "Size of another vector of the "
67  "random variable", size_y_old);
68  size_y_old = size_y_new;
69  }
70  int size_mu_old = size_mu;
71  int size_mu_new;
72  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
73  int size_mu_new = mu_vec[i].size();
74  check_size_match(function,
75  "Size of one of the vectors of "
76  "the location variable", size_mu_new,
77  "Size of another vector of the "
78  "location variable", size_mu_old);
79  size_mu_old = size_mu_new;
80  }
81  (void) size_y_old;
82  (void) size_y_new;
83  (void) size_mu_old;
84  (void) size_mu_new;
85  }
86 
87  check_size_match(function,
88  "Size of random variable", size_y,
89  "size of location parameter", size_mu);
90  check_size_match(function,
91  "Size of random variable", size_y,
92  "rows of covariance parameter", Sigma.rows());
93  check_size_match(function,
94  "Size of random variable", size_y,
95  "columns of covariance parameter", Sigma.cols());
96 
97  for (size_t i = 0; i < size_vec; i++) {
98  check_finite(function, "Location parameter", mu_vec[i]);
99  check_not_nan(function, "Random variable", y_vec[i]);
100  }
101 
102  if (size_y == 0) // y_vec[0].size() == 0
103  return lp;
104 
106  lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;
107 
109  lp -= 0.5 * log_determinant_ldlt(ldlt_Sigma) * size_vec;
110 
112  lp_type sum_lp_vec(0.0);
113  for (size_t i = 0; i < size_vec; i++) {
114  Eigen::Matrix<typename return_type<T_y, T_loc>::type, Dynamic, 1>
115  y_minus_mu(size_y);
116  for (int j = 0; j < size_y; j++)
117  y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
118  sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_minus_mu);
119  }
120  lp -= 0.5*sum_lp_vec;
121  }
122  return lp;
123  }
124 
125  template <typename T_y, typename T_loc, typename T_covar>
126  inline
128  multi_normal_log(const T_y& y,
129  const T_loc& mu,
130  const T_covar& Sigma) {
131  return multi_normal_log<false>(y, mu, Sigma);
132  }
133 
134  }
135 }
136 
137 #endif
size_t max_size_mvt(const T1 &x1, const T2 &x2)
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt(const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
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
size_t size_
Definition: dot_self.hpp:18
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
return_type< T_y, T_loc, T_covar >::type multi_normal_log(const T_y &y, const T_loc &mu, const T_covar &Sigma)
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.

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