Interfaces for the NAG Mark 27.1 rnla Chapter.
rnla - Randomized Numerical Linear Algebra
This module covers linear algebra functions that make use of random projections to reduce problem dimension. This area is referred to as RNLA (Randomized Numerical Linear Algebra). The functions can be split into the following categories:
building blocks that are intended to be used as components in RNLA algorithms written by you;
RNLA algorithms for matrix factorization.
It is envisaged that users of the higher-level functions, such as matrix factorization, will have some background in linear algebra.
A common use case would be that you have tried solving your problem using a deterministic linear algebra function, e.g., an LAPACK function from submodule
lapackeig, and are in need of a function that is more computationally efficient.
Users of the building block functions would be expected to have some familiarity with the RNLA literature, i.e., a higher level of expertise.
random projection with DCT (float):
SVD via row extraction (float):
For full information please refer to the NAG Library document