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A Short Excursion into Matrix Algebra

Wolfgang Karl Härdle () and Leopold Simar
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Wolfgang Karl Härdle: Humboldt-Universität zu Berlin, Ladislaus von Bortkiewicz Chair of Statistics

Chapter Chapter 2 in Applied Multivariate Statistical Analysis, 2019, pp 47-69 from Springer

Abstract: Abstract This chapter serves as 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 Sect. 2.2 and 2.3, we present the spectral decomposition of matrices and consider the maximization (minimization) of quadratic forms given some constraints.

Date: 2019
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Related works:
Chapter: A Short Excursion into Matrix Algebra (2024)
Chapter: A Short Excursion into Matrix Algebra (2015)
Chapter: A Short Excursion into Matrix Algebra (2003)
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DOI: 10.1007/978-3-030-26006-4_2

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