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Advanced Studies in Behaviormetrics and Data Science: Essays in Honor of Akinori Okada /

Advanced Studies in Behaviormetrics and Data Science: Essays in Honor of Akinori Okada /
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Field name Details
Dewey Class 519.5
Title Advanced Studies in Behaviormetrics and Data Science ([EBook]) : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama.
Added Personal Name Imaizumi, Tadashi
Nakayama, Atsuho
Yokoyama, Satoru
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2020.
Publication Singapore : : Springer Singapore : : Imprint: Springer, , 2020.
Physical Details XV, 472 p. 136 illus., 69 illus. in color. : online resource.
Series Behaviormetrics: Quantitative Approaches to Human Behavior 2524-4027 ; ; 5
ISBN 9789811527005
Summary Note This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts. .:
Contents note Co-clustering for object by variable data matrices -- How to use the Hermitian Form Model for asymmetric MDS -- Asymmetric scaling models for square contingency tables: points, circles, arrows, and odds ratios -- Comparing partitions of the Petersen graph -- Minkowski distances and standardisation for clustering and classification on high dimensional data. .
Mode of acces to digital resource Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
System details note - Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site https://doi.org/10.1007/978-981-15-2700-5
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