Hello, I am working on square root factorization of the matrix of the form A = I + U'U which is typically positive semi-definite of dimension N \sim 100. I need to solve a least square problem A^{-1}Y and compute the product \sqrt{A^{-1}} R, where Y a non-square matrix and R an orthogonal matrix. …

So to put this all together, here’s how I understand this should be approached. You can use your favorite factorization as it suits you. I tested svd and eigen and found svd was a bit slower, but as Antoine said, it can be more stable: using Random, RandomMatrices function f1(A, Y, R) (op1=A\Y…

Square root of the inverse of a matrix

Specific Domains Numerics

jlchan June 16, 2020, 6:30pm 2

If the matrix is symmetric positive definite, how about pre computing the eigen decomposition and using that to compute both the inverse and square root?

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Square root of the inverse of a matrix

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