Mathematics Books
Linear algebra, matrix theory, and calculus foundations
⭐ Essential Reading
(1 book)
Matrix Algebra Useful for Statistics
Shayle R. Searle, Andre I. Khuri (2017)
Comprehensive treatment of matrix algebra concepts essential for understanding statistical methods. Covers matrix operations, eigenvalues, generalized inverses, and applications to statistics. Second edition.
ISBN: 978-1118935149
This book may be available from your University library website
👍 Recommended
(2 books)
Linear Algebra for Data Science
Sorin Mitran
Accessible introduction to linear algebra concepts with applications to data science. From University of North Carolina at Chapel Hill. Free PDF available.
A First Course in Linear Algebra
Robert A. Beezer
Comprehensive first course in linear algebra from University of Puget Sound. Open textbook with clear explanations suitable for beginners. Version 3.50. Free PDF available.
💡 Learning Path
Essential Foundation: Searle & Khuri's "Matrix Algebra Useful for Statistics" provides the mathematical foundation needed for understanding linear models and mixed model equations.
Key Topics: Matrix operations, eigenvalues and eigenvectors, generalized inverses, and matrix decompositions are fundamental to animal breeding methods.
Application: Matrix algebra is essential for understanding Henderson's mixed model equations, relationship matrices (A, G, H), and variance component estimation.