svd() [1/2]

template<typename EigMat , require_eigen_matrix_dynamic_t< EigMat > * = nullptr, require_not_st_var< EigMat > * = nullptr>

std::tuple< Eigen::Matrix< value_type_t< EigMat >, -1, -1 >, Eigen::Matrix< base_type_t< EigMat >, -1, 1 >, Eigen::Matrix< value_type_t< EigMat >, -1, -1 > > stan::math::svd

(

const EigMat &

m

)

Given input matrix m, return the singular value decomposition (U,D,V) such that m = U*diag(D)*V^{T}

Template Parameters

EigMat

type of the matrix

Parameters

m	MxN input matrix

Returns

a tuple (U,D,V) where U is an orthogonal matrix, D a vector of singular values (in decreasing order), and V an orthogonal matrix

Definition at line 24 of file svd.hpp.