topic you can do that by using in Intel® oneAPI Math Kernel Library

How to compute covariance matrix in MKL?

Hai — Fri, 18 Jan 2013 21:09:17 GMT

Given a 2D matrix A as input, how to compute its covariance matrix? For example, in Matlab, I use cov(A) to do the computation.

Thanks

you can do that by using

Gennady_F_Intel — Sat, 19 Jan 2013 06:58:40 GMT

you can do that by using Summary Statistical Functions. Vslsssnewtask(&task, p, n, xstorage, x, w, indices) where P -- Dimension of the task, number of variables

There are many examples show how to do that. You can find these examples into manual or into <mkl_root>\examples\vsls\source\"

More specifically you should

Ilya_B_Intel — Wed, 23 Jan 2013 07:19:00 GMT

More specifically you should be interested in vslsbasicstats.c/vsldbasicstats.c for C or vslsbasicstats.f/vsldbasicstats.f for Fortran examples.

At the same time those examples show calculation for all basic stats including min/max, moments, skewness, etc.

In order to calculate covariance only you can skip several steps there, the rest will be: vslsSSNewTask() + vslsSSEditCovCor() + vslsSSCompute() + vslSSDeleteTask().

You can also look here:

Summary Statistics Application Notes, and especially this part is about calculation cov/cor and meaning of each step.
There is also an older blog post, which gives some insight for use case.