| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA996418190803316 |
|
|
Titolo |
Advanced Studies in Behaviormetrics and Data Science [[electronic resource] ] : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2020.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (XV, 472 p. 136 illus., 69 illus. in color.) |
|
|
|
|
|
|
Collana |
|
Behaviormetrics: Quantitative Approaches to Human Behavior, , 2524-4027 ; ; 5 |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Statistics |
Motivation research (Marketing) |
Mathematics |
Visualization |
Social sciences |
Psychometrics |
Statistics for Social Sciences, Humanities, Law |
Statistical Theory and Methods |
Consumer Behavior |
Methodology of the Social Sciences |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
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. . |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
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. . |
|
|
|
|
|
| |