Three-Way Partial Correlation Measures

Vicari, Donatella

doi:10.1007/978-3-642-59789-3_45

Donatella Vicari⁸

Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization ((STUDIES CLASS))

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Abstract

Analysis of linear relations between variables, given a third one, can be investigated for three-way three-mode data, by defining new measures of linear dependence between occasions. In this paper, two partial correlation coefficients between matrices are proposed. Their properties are analyzed, in particular with respect to the absence of conditional linear dependence.

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Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università di Roma “La Sapienza”, Italy
Donatella Vicari

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Donatella Vicari
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Editors and Affiliations

University of Groningen Heymans Institute (PA), Grote Kruisstraat 2/1, NL-9712 TS, Groningen, The Netherlands
Henk A. L. Kiers
Facultés Universitaires Notre-Dame de la Paix, University of Namur, Rempart de la Vierge, 8, B-5000, Namur, Belgium
Jean-Paul Rasson (Directeur du Department de Mathématique) (Directeur du Department de Mathématique)
Data Theory Group Department of Education, Leiden University, P.O. Box 9555, NL-2300 RB, Leiden, The Netherlands
Patrick J. F. Groenen
Lehrstuhl für Wirtschaftsinformatik III Schloß, University of Mannheim, D-68131, Mannheim, Germany
Martin Schader

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Vicari, D. (2000). Three-Way Partial Correlation Measures. In: Kiers, H.A.L., Rasson, JP., Groenen, P.J.F., Schader, M. (eds) Data Analysis, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59789-3_45

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DOI: https://doi.org/10.1007/978-3-642-59789-3_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67521-1
Online ISBN: 978-3-642-59789-3
eBook Packages: Springer Book Archive

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