Linear Algebra and Matrix Analysis for Statistics

Citations Over TimeTop 10% of 2014 papers

Abstract

Assuming no prior knowledge of linear algebra, this self-contained text offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book covers important topics in linear algebra that are useful for statisticians, including the concept of rank, the fundamental theorem of linear algebra, projectors, and quadratic forms. It also provides an extensive collection of exercises on theoretical concepts and numerical computations.

Related Papers

• → Applied Linear Algebra and Matrix Analysis(2007)93 cited
• Matrix Methods: Applied Linear Algebra(2008)
• → Computer algebra tailored to matrix inequalities in control(2004)5 cited
• → Vector and Matrix Operations(1994)1 cited
• The Analysis of Several Questions That Is in Liner Algebra(2005)