Automatic Differentiation
 
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◆ cov_matrix_constrain() [3/5]

template<bool Jacobian, typename T , require_not_std_vector_t< T > * = nullptr>
auto stan::math::cov_matrix_constrain ( const T &  x,
Eigen::Index  K,
return_type_t< T > &  lp 
)
inline

Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2).

If the Jacobian parameter is true, the log density accumulator is incremented with the log absolute Jacobian determinant of the transform. All of the transforms are specified with their Jacobians in the Stan Reference Manual chapter Constraint Transforms.

Template Parameters
Jacobianif true, increment log density accumulator with log absolute Jacobian determinant of constraining transform
TA type inheriting from Eigen::DenseBase or a var_value with inner type inheriting from Eigen::DenseBase with compile time dynamic rows and 1 column
Parameters
xThe vector to convert to a covariance matrix
KThe dimensions of the resulting covariance matrix
[in,out]lplog density accumulator
Exceptions
std::domain_errorif (x.size() != K + (K choose 2)).

If the Jacobian parameter is true, the log density accumulator is incremented with the log absolute Jacobian determinant of the transform. All of the transforms are specified with their Jacobians in the Stan Reference Manual chapter Constraint Transforms.

Template Parameters
Jacobianif true, increment log density accumulator with log absolute Jacobian determinant of constraining transform
TA standard vector with inner type inheriting from Eigen::DenseBase or a var_value with inner type inheriting from Eigen::DenseBase with compile time dynamic rows and 1 column
Parameters
xThe vector to convert to a covariance matrix
KThe dimensions of the resulting covariance matrix
[in,out]lplog density accumulator
Exceptions
std::domain_errorif (x.size() != K + (K choose 2)).

Definition at line 108 of file cov_matrix_constrain.hpp.