A Short Excursion into Matrix Algebra

Wolfgang Härdle () and Leopold Simar
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Wolfgang Härdle: Humboldt-Universität zu Berlin, CASE — Center for Applied Statistics and Economics, Institut für Statistik und Ökonometrie

Chapter 2 in Applied Multivariate Statistical Analysis, 2003, pp 57-80 from Springer

Abstract: Abstract This chapter is a reminder of basic concepts of matrix algebra, which are particularly useful in multivariate analysis. It also introduces the notations used in this book for vectors and matrices. Eigenvalues and eigenvectors play an important role in multivariate techniques. In Sections 2.2 and 2.3, we present the spectral decomposition of matrices and consider the maximization (minimization) of quadratic forms given some constraints.

Keywords: Quadratic Form; Null Space; Spectral Decomposition; Projection Matrix; Generalize Inverse (search for similar items in EconPapers)
Date: 2003
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Chapter: A Short Excursion into Matrix Algebra (2024)
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DOI: 10.1007/978-3-662-05802-2_2

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