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 Sects. 2.2 and 2.3, we present the spectral decomposition of matrices and consider the maximisation (minimisation) of quadratic forms given some constraints.
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© 2015 Springer-Verlag Berlin Heidelberg
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Härdle, W.K., Simar, L. (2015). A Short Excursion into Matrix Algebra. In: Applied Multivariate Statistical Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45171-7_2
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DOI: https://doi.org/10.1007/978-3-662-45171-7_2
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-662-45171-7
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