Abstract
There is no way to survive in the middle of statistical considerations without being pretty well aware of the main properties of the eigenvalues and eigenvectors. This chapter provides a summary of some central results.
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© 2011 Springer-Verlag Berlin Heidelberg
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Puntanen, S., Styan, G.P.H., Isotalo, J. (2011). Eigenvalue Decomposition. In: Matrix Tricks for Linear Statistical Models. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10473-2_19
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DOI: https://doi.org/10.1007/978-3-642-10473-2_19
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10472-5
Online ISBN: 978-3-642-10473-2
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