Abstract
In Chap. 1 basic descriptive techniques were developed which provided tools for “looking” at multivariate data. They were based on adaptations of bivariate or univariate devices used to reduce the dimensions of the observations. In the following three chapters, issues of reducing the dimension of a multivariate data set will be discussed. The perspectives will be different but the tools will be related.
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© 2015 Springer-Verlag Berlin Heidelberg
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Härdle, W.K., Simar, L. (2015). Decomposition of Data Matrices by Factors. In: Applied Multivariate Statistical Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45171-7_10
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DOI: https://doi.org/10.1007/978-3-662-45171-7_10
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45170-0
Online ISBN: 978-3-662-45171-7
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