Applied matrix and tensor variate data analysis / Toshio Sakata, editor.

Other author Sakata, Toshio, 1951-
Format Electronic
Publication Info[Japan] : Springer, [2016]
Descriptionxi, 136 pages : illustrations (some color) 24 cm.
Supplemental ContentFull text available from Springer Books
Supplemental ContentFull text available from Springer Nature - Springer Mathematics and Statistics eBooks 2016 English International
Subjects

SeriesSpringerBriefs in statistics
JSS research series in statistics
SpringerBriefs in statistics.
JSS research series in statistics.
Abstract This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate and tensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics.
Bibliography noteIncludes bibliographical references.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Issued in other formElectronic version: Applied matrix and tensor variate data analysis. [Japan] : Springer, 2016 9784431553878
Genre/formElectronic books.
LCCN 2015959581
ISBN9784431553861 (paperback : acid-free paper)
ISBN443155386X (paperback : acid-free paper)

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