cov_matrix_free.hpp

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#ifndef STAN_MATH_PRIM_FUN_COV_MATRIX_FREE_HPP
#define STAN_MATH_PRIM_FUN_COV_MATRIX_FREE_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/log.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <cmath>
 
namespace stan {
namespace math {
 
template <typename T, require_eigen_t<T>* = nullptr>
Eigen::Matrix<value_type_t<T>, Eigen::Dynamic, 1> cov_matrix_free(const T& y) {
  const auto& y_ref = to_ref(y);
  check_square("cov_matrix_free", "y", y_ref);
  check_nonzero_size("cov_matrix_free", "y", y_ref);
 
  using std::log;
  int K = y_ref.rows();
  check_positive("cov_matrix_free", "y", y_ref.diagonal());
  Eigen::Matrix<value_type_t<T>, Eigen::Dynamic, 1> x((K * (K + 1)) / 2);
  // FIXME: see Eigen LDLT for rank-revealing version -- use that
  // even if less efficient?
  Eigen::LLT<plain_type_t<T>> llt(y_ref.rows());
  llt.compute(y_ref);
  plain_type_t<T> L = llt.matrixL();
  int i = 0;
  for (int m = 0; m < K; ++m) {
    x.segment(i, m) = L.row(m).head(m);
    i += m;
    x.coeffRef(i++) = log(L.coeff(m, m));
  }
  return x;
}
 
template <typename T, require_std_vector_t<T>* = nullptr>
auto cov_matrix_free(const T& x) {
  return apply_vector_unary<T>::apply(
      x, [](auto&& v) { return cov_matrix_free(v); });
}
 
}  // namespace math
}  // namespace stan
 
#endif