Linear Regression without computing pseudo-inverse matrix

2013/11/06 by Demetris Christopoulos, Demetris T. Christopoulos, Christopoulos, Demetris T.
Agricultural and Biological Sciences · Mathematics · #Advanced Scientific Research Methods #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Primary 97K80 #Secondary 62J05 #Statistics Theory (math.ST) #math.ST #msc:62J05 #msc:97K80 #stat.CO #stat.TH

paper · pdf · doi:10.48550/arxiv.1311.1835

4 pages

arxiv created 2013/11/06 · openalex publication_date 2013/11/06 · arxiv updated 2013/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We are presenting a method of linear regression based on Gram-Schmidt orthogonal projection that does not compute a pseudo-inverse matrix. This is useful when we want to make several regressions with random data vectors for simulation purposes.

Citations

• A generalized inverse for matrices

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