Stan Math Library  2.11.0
reverse mode automatic differentiation
multi_normal_cholesky_log.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
3 
22 #include <boost/random/normal_distribution.hpp>
23 #include <boost/random/variate_generator.hpp>
24 
25 namespace stan {
26  namespace math {
44  template <bool propto,
45  typename T_y, typename T_loc, typename T_covar>
46  typename return_type<T_y, T_loc, T_covar>::type
48  const T_loc& mu,
49  const T_covar& L) {
50  static const char* function("stan::math::multi_normal_cholesky_log");
51  typedef typename scalar_type<T_covar>::type T_covar_elem;
52  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
53  lp_type lp(0.0);
54 
59  using stan::math::sum;
60 
64 
65  VectorViewMvt<const T_y> y_vec(y);
66  VectorViewMvt<const T_loc> mu_vec(mu);
67  // size of std::vector of Eigen vectors
68  size_t size_vec = max_size_mvt(y, mu);
69 
70  // Check if every vector of the array has the same size
71  int size_y = y_vec[0].size();
72  int size_mu = mu_vec[0].size();
73  if (size_vec > 1) {
74  int size_y_old = size_y;
75  int size_y_new;
76  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
77  int size_y_new = y_vec[i].size();
78  check_size_match(function,
79  "Size of one of the vectors of "
80  "the random variable", size_y_new,
81  "Size of another vector of the "
82  "random variable", size_y_old);
83  size_y_old = size_y_new;
84  }
85  int size_mu_old = size_mu;
86  int size_mu_new;
87  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
88  int size_mu_new = mu_vec[i].size();
89  check_size_match(function,
90  "Size of one of the vectors of "
91  "the location variable", size_mu_new,
92  "Size of another vector of the "
93  "location variable", size_mu_old);
94  size_mu_old = size_mu_new;
95  }
96  (void) size_y_old;
97  (void) size_y_new;
98  (void) size_mu_old;
99  (void) size_mu_new;
100  }
101 
102  check_size_match(function,
103  "Size of random variable", size_y,
104  "size of location parameter", size_mu);
105  check_size_match(function,
106  "Size of random variable", size_y,
107  "rows of covariance parameter", L.rows());
108  check_size_match(function,
109  "Size of random variable", size_y,
110  "columns of covariance parameter", L.cols());
111 
112  for (size_t i = 0; i < size_vec; i++) {
113  check_finite(function, "Location parameter", mu_vec[i]);
114  check_not_nan(function, "Random variable", y_vec[i]);
115  }
116 
117  if (size_y == 0)
118  return lp;
119 
121  lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;
122 
124  lp -= L.diagonal().array().log().sum() * size_vec;
125 
127  lp_type sum_lp_vec(0.0);
128  for (size_t i = 0; i < size_vec; i++) {
129  Eigen::Matrix<typename return_type<T_y, T_loc>::type,
130  Eigen::Dynamic, 1> y_minus_mu(size_y);
131  for (int j = 0; j < size_y; j++)
132  y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
133  Eigen::Matrix<typename return_type<T_y, T_loc, T_covar>::type,
134  Eigen::Dynamic, 1>
135  half(mdivide_left_tri_low(L, y_minus_mu));
136  // FIXME: this code does not compile. revert after fixing subtract()
137  // Eigen::Matrix<typename
138  // boost::math::tools::promote_args<T_covar,
139  // typename value_type<T_loc>::type,
140  // typename value_type<T_y>::type>::type>::type,
141  // Eigen::Dynamic, 1>
142  // half(mdivide_left_tri_low(L, subtract(y, mu)));
143  sum_lp_vec += dot_self(half);
144  }
145  lp -= 0.5*sum_lp_vec;
146  }
147  return lp;
148  }
149 
150  template <typename T_y, typename T_loc, typename T_covar>
151  inline
153  multi_normal_cholesky_log(const T_y& y, const T_loc& mu, const T_covar& L) {
154  return multi_normal_cholesky_log<false>(y, mu, L);
155  }
156 
157  }
158 }
159 #endif
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
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.
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
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_covar >::type multi_normal_cholesky_log(const T_y &y, const T_loc &mu, const T_covar &L)
The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the varian...
size_t size_
Definition: dot_self.hpp:18
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
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12

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