This is an implementation of Cholesky decomposition based on . The algorithm exploits matrix multiplication and is consequently faster than the canonical implementations of Cholesky decomposition via Cholesky-Banachiewicz/Cholesky-Crout decompositions, which use only matrix-vector multiplication (and not matrix-matrix multiplication). Interestingly enough, the algorithm can be seen as a hybrid between Cholesky-Banachiewicz and Cholesky-Crout algorithms. The algorithm takes a parameter, which says how large should be the matrix for matrix multiplication. If no parameter is passed, an optimal size for matrix multiplication is estimated.
The package contains following algorithms:
A practical note: Neither of the implementations is faster than the build in 'chol' function. The provided methods are merely for educative purposes.
 Simple, Fast and Practicable Algorithms for Cholesky, LU and QR Decomposition Using Fast Rectangular Matrix Multiplication by Cristóbal Camarero
Jan Motl (2020). Cholesky decomposition (https://www.mathworks.com/matlabcentral/fileexchange/71304-cholesky-decomposition), MATLAB Central File Exchange. Retrieved .