1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP 2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP 23 #include <boost/random/normal_distribution.hpp> 24 #include <boost/random/variate_generator.hpp> 45 template <
bool propto,
46 typename T_y,
typename T_loc,
typename T_covar>
51 static const char*
function(
"multi_normal_cholesky_log");
61 int size_y = y_vec[0].size();
62 int size_mu = mu_vec[0].size();
64 int size_y_old = size_y;
67 int size_y_new = y_vec[i].size();
69 "Size of one of the vectors of " 70 "the random variable", size_y_new,
71 "Size of another vector of the " 72 "random variable", size_y_old);
73 size_y_old = size_y_new;
75 int size_mu_old = size_mu;
78 int size_mu_new = mu_vec[i].size();
80 "Size of one of the vectors of " 81 "the location variable", size_mu_new,
82 "Size of another vector of the " 83 "location variable", size_mu_old);
84 size_mu_old = size_mu_new;
93 "Size of random variable", size_y,
94 "size of location parameter", size_mu);
96 "Size of random variable", size_y,
97 "rows of covariance parameter", L.rows());
99 "Size of random variable", size_y,
100 "columns of covariance parameter", L.cols());
102 for (
size_t i = 0; i < size_vec; i++) {
103 check_finite(
function,
"Location parameter", mu_vec[i]);
114 lp -= L.diagonal().array().log().sum() * size_vec;
117 lp_type sum_lp_vec(0.0);
118 for (
size_t i = 0; i < size_vec; i++) {
119 Eigen::Matrix<typename return_type<T_y, T_loc>::type,
120 Eigen::Dynamic, 1> y_minus_mu(size_y);
121 for (
int j = 0; j < size_y; j++)
122 y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
123 Eigen::Matrix<typename return_type<T_y, T_loc, T_covar>::type,
135 lp -= 0.5*sum_lp_vec;
140 template <
typename T_y,
typename T_loc,
typename T_covar>
144 return multi_normal_cholesky_log<false>(y, mu, L);
void check_finite(const char *function, const char *name, const T_y &y)
Check if y is finite.
size_t max_size_mvt(const T1 &x1, const T2 &x2)
scalar_type_helper< is_vector< T >::value, T >::type type
void check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Check if the provided sizes match.
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
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
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...
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
const double NEG_LOG_SQRT_TWO_PI
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)
VectorViewMvt is a template expression that wraps either an Eigen::Matrix or a std::vector<Eigen::Mat...
size_t length_mvt(const Eigen::Matrix< T, R, C > &)