European University Institute Library

Advanced Studies in Behaviormetrics and Data Science, Essays in Honor of Akinori Okada, edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama

Label
Advanced Studies in Behaviormetrics and Data Science, Essays in Honor of Akinori Okada, edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama
Language
eng
resource.imageBitDepth
0
Literary Form
non fiction
Main title
Advanced Studies in Behaviormetrics and Data Science
Medium
electronic resource
Nature of contents
dictionaries
Oclc number
1152054865
Responsibility statement
edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama
Series statement
Behaviormetrics: Quantitative Approaches to Human Behavior,, 5, 2524-4027Springer eBooks.
Sub title
Essays in Honor of Akinori Okada
Summary
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.--, Provided by publisher
Table Of Contents
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.
Content
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