Matrix Factorization
Abstract
This chapter presents some commonly used matrix factorization (decomposition) methods in reducing and transforming system of linear equations (including least squares) into simpler forms QR, LU, and Cholesky. In this presentation, the following are presented: Brief and sufficient mathematical descriptions with examples are given for the respective methods, as well as the relevant concepts (pivoting, matrix symmetry, and positive definiteness). In-place references are included, for further reading. C++ implementations, using the Eigen library, are provided.
Fields of Study & Subjects
Matrix Theory and Algorithms
Statistical and numerical algorithms
Numerical Methods and Algorithms
Publication details
- Journal / source
- Chapman & Hall/CRC eBooks
- Pages
- 40–67
- Publication date
- 28 January 2026
- Language
- EN
- Document type
- Book chapter