Hi, I’m working with a larger algorithm in which a recurring step (done 5 - 20 times) is to carry out a linear regression y^k = X\beta^k + \varepsilon^k with roughly 100.000 observations and 1.000-5.000 variables, where y^k is either a length 100.000 vector or 100.000 by 1.000 matrix that depends o…

[image] JADekker: As such, I’d like to save some computational effort and recycle some work if possible. The thing that comes to mind is to compute pinv(X) and to carry out the regression as pinv(X)*y^k. I was wondering if this is the way to go here, or if there is a better approach that I’m mis…

Repeated linear least squares problem with large dimensions

General Usage Performance

stevengj Split this topic June 19, 2025, 9:24pm 8

4 posts were split to a new topic: Repeated high (6–7) dimensional interpolation

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Result changes depending on whether matrix is sparse or not General Usage linearalgebra	16	2531	November 4, 2019
Use QR factorization efficiently Performance linearalgebra	12	5263	January 27, 2018
Optimzing many linear solves Performance	2	280	June 14, 2023
Linear least-squares solution occasionally much slower than what is achievable using LAPACK based wrappers General Usage	0	440	July 19, 2020
Moore-Penrose Generalized Inverse of Sparse Matrix Optimization (Mathematical)	2	3566	November 12, 2018

Repeated linear least squares problem with large dimensions

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