| linalg_cholesky {torch} | R Documentation |
Computes the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix.
Description
Letting \mathbb{K} be \mathbb{R} or \mathbb{C},
the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix
A \in \mathbb{K}^{n \times n} is defined as
Usage
linalg_cholesky(A)
Arguments
A |
(Tensor): tensor of shape |
Details
Math could not be displayed. Please visit the package website.
where L is a lower triangular matrix and
L^{H} is the conjugate transpose when L is complex, and the
transpose when L is real-valued.
Supports input of float, double, cfloat and cdouble dtypes.
Also supports batches of matrices, and if A is a batch of matrices then
the output has the same batch dimensions.
See Also
-
linalg_cholesky_ex()for a version of this operation that skips the (slow) error checking by default and instead returns the debug information. This makes it a faster way to check if a matrix is positive-definite.linalg_eigh()for a different decomposition of a Hermitian matrix. The eigenvalue decomposition gives more information about the matrix but it slower to compute than the Cholesky decomposition.
Other linalg:
linalg_cholesky_ex(),
linalg_det(),
linalg_eigh(),
linalg_eigvalsh(),
linalg_eigvals(),
linalg_eig(),
linalg_householder_product(),
linalg_inv_ex(),
linalg_inv(),
linalg_lstsq(),
linalg_matrix_norm(),
linalg_matrix_power(),
linalg_matrix_rank(),
linalg_multi_dot(),
linalg_norm(),
linalg_pinv(),
linalg_qr(),
linalg_slogdet(),
linalg_solve_triangular(),
linalg_solve(),
linalg_svdvals(),
linalg_svd(),
linalg_tensorinv(),
linalg_tensorsolve(),
linalg_vector_norm()
Examples
if (torch_is_installed()) {
a <- torch_eye(10)
linalg_cholesky(a)
}