1 #ifndef STAN_MATH_PRIM_FUN_READ_CORR_MATRIX_HPP
2 #define STAN_MATH_PRIM_FUN_READ_CORR_MATRIX_HPP
3
4 #include <stan/math/prim/fun/Eigen.hpp>
5 #include <stan/math/prim/fun/read_corr_L.hpp>
6 #include <stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp>
7
8 namespace stan {
9 namespace math {
10
11 /**
12 * Return the correlation matrix of the specified dimensionality
13 * corresponding to the specified canonical partial correlations.
14 *
15 * <p>See <code>read_corr_matrix(Array, size_t, T)</code>
16 * for more information.
17 *
18 * @tparam T_CPCs type of the array (must be derived from \c Eigen::ArrayBase
19 * and have one compile-time dimension equal to 1)
20 * @param CPCs The (K choose 2) canonical partial correlations in (-1, 1).
21 * @param K Dimensionality of correlation matrix.
22 * @return Cholesky factor of correlation matrix for specified
23 * canonical partial correlations.
24 */
25 template <typename T_CPCs, require_eigen_vector_t<T_CPCs>* = nullptr>
26 Eigen::Matrix<value_type_t<T_CPCs>, Eigen::Dynamic, Eigen::Dynamic>
read_corr_matrix(const T_CPCs & CPCs,size_t K)27 read_corr_matrix(const T_CPCs& CPCs, size_t K) {
28 if (K == 0) {
29 return {};
30 }
31
32 return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K));
33 }
34
35 /**
36 * Return the correlation matrix of the specified dimensionality
37 * corresponding to the specified canonical partial correlations,
38 * incrementing the specified scalar reference with the log
39 * absolute determinant of the Jacobian of the transformation.
40 *
41 * It is usually preferable to utilize the version that returns
42 * the Cholesky factor of the correlation matrix rather than the
43 * correlation matrix itself in statistical calculations.
44 *
45 * @tparam T_CPCs type of the array (must be derived from \c Eigen::ArrayBase
46 * and have one compile-time dimension equal to 1)
47 * @param CPCs The (K choose 2) canonical partial correlations in
48 * (-1, 1).
49 * @param K Dimensionality of correlation matrix.
50 * @param log_prob Reference to variable to increment with the log
51 * Jacobian determinant.
52 * @return Correlation matrix for specified partial correlations.
53 */
54 template <typename T_CPCs, require_eigen_vector_t<T_CPCs>* = nullptr>
55 Eigen::Matrix<value_type_t<T_CPCs>, Eigen::Dynamic, Eigen::Dynamic>
read_corr_matrix(const T_CPCs & CPCs,size_t K,value_type_t<T_CPCs> & log_prob)56 read_corr_matrix(const T_CPCs& CPCs, size_t K, value_type_t<T_CPCs>& log_prob) {
57 if (K == 0) {
58 return {};
59 }
60
61 return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
62 }
63
64 } // namespace math
65 } // namespace stan
66
67 #endif
68