\sa MatrixBase::coeff() * \warning the coordinates must fit into the referenced triangular part */

\returns the coefficient value at given position \a row, \a col * This operation involes a log(rho*outer_size) binary search. */

! * This overrides ReturnByValue::coeff because this function is * efficient enough. */

* Number of columns */

\returns the number of rows */

\returns the number of columns */

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Returns the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

Return the number of columns of the underlying matrix.

* Compute the left and right diagonal matrices to scale the input matrix @p mat * * FIXME This algorithm will be modified such that the dia

Conducts the major computation procedure. \param selection An enumeration value indicating the selection rule of the requested eigenvalues, for exam

Compute the QR decomposition of a tridiagonal matrix with an optional shift. \param mat Matrix type can be `Eigen::Matrix<Scalar, ...>` (e.g. `Eigen:

Given x and y, compute 1) r = sqrt(x^2 + y^2), 2) c = x / r, 3) s = -y / r If both x and y are zero, set c = 1 and s = 0 We must implement it in a num

Concordance index for right-censored data Reference from scikit-survival: `sksurv.metrics.concordance_index_censored`. The concordance i

\returns a const pointer to the column major internal matrix */

replace B by C in A to do : binary search

Returns the converged eigenvalues. \return A vector containing the eigenvalues. Returned vector type will be `Eigen::Vector<Scalar, ...>`, depending

Returns the eigenvectors associated with the converged eigenvalues. \param nvec The number of eigenvectors to return. \return A matrix containing th

compares evaluations against known results */

compares evaluations on corner cases */

Given orthonormal basis V (w.r.t. B), find a nonzero vector f such that V'Bf = 0 With rounding errors, we hope V'B(f/||f||) < eps Assume that f has be

Append new vectors to the search space and orthogonalize the resulting matrix \param new_vect Matrix of new correction vectors