Akinori Okada – författare

This volume focuses on innovative approaches and recent developments in clustering, analysis of data and models, and applications: The first part of the book covers a broad range of innovations in the area of clustering, from algorithmic innovations for graph clustering to new visualization and evaluation techniques. The second part addresses new developments in data and decision analysis (conjoint analysis, non-additive utility functions, analysis of asymmetric relationships, and regularization techniques). The third part is devoted to the application of innovative data analysis methods in the life-sciences, the social sciences and in engineering. All contributions in this volume are revised and extended versions of selected papers presented in the German/Japanese Workshops at Karlsruhe (2010) and Kyoto (2012).

This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate. The challenging proposals provide a connection between statistical methodology and the social domain with particular attention to computational issues in order to effectively address complicated data analysis problems.The papers in this volume stem from contributions initially presented at the joint international meeting JCS-CLADAG held in Anacapri (Italy) where the Japanese Classification Society and the Classification and Data Analysis Group of the Italian Statistical Society had a stimulating scientific discussion and exchange.

This volume contains selected papers presented at two joint German-Japanese symposia on data analysis and related elds. The articles substantially extend and further develop material presented at the two symposia organized on the basis of longstanding and close relationships which have been cultivated in the last couple of decades between the two classi cation societies: the German Class- cation Society (Gesellschaft fu ..r Klassi kation e. V.) and the Japanese Classi cation Society. These symposia have been very helpful in exchanging ideas, views, and knowledge between the two societies and have served as a spring board for more extensive and closer co-operation between the societies as well as among their individual members. The scienti c program of the rst Joint Japanese-German Symposium (Tokyo 2005)included23presentations;forthesecondJointGerman-JapaneseSymposium (Berlin 2006) 27 presentations were scheduled. This volume presents 21 peer refereed papers, which are grouped into three parts: 1. Part 1 Clustering and Visualization (eight papers) 2. Part 2 Methods in Fields (nine papers) 3.Part 3 Applications in Clustering and Visualization (four papers) The concept of having a joint symposium of the two classi cation societies came from the talks with Hans-Hermann and Wolfgang when Akinori attended the 28th Annual Conference of the German Classi cation Society held in Dortmund in March 2004.

At the International Meeting of the Psychometric Society in Osaka, Japan, more than 300 participants from 19 countries gathered to discuss recent developments in the theory and application of psychometrics.

This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines.In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered.The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data.

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data.

This informative book demonstrates the analyses of data from diverse areas to show how asymmetric relationships are prevalent in real-world relationships and helps readers grasp the meanings and implications of those relationships.

This is the first book that focusses the attention on applying asymmetric multidimensional scaling (MDS) and describes how to apply it in a practical manner. The book provides the know-how for prominent methods of asymmetric MDS: analysis of asymmetric relationships and the efficient use of programs of asymmetric MDS based on a distance model. These features will facilitate the work of researchers and enlighten students in disciplines such as statistics, psychology, sociology, education, marketing science, medicine, education, and other fields. Support is provided for practitioners in these areas who are, for instance, developing new products or services, investigating dominance relationships among brands or products, researching the use of antibiotics against resistance bacteria, and developing items for tests. This informative book demonstrates the analyses of data from diverse areas to show how asymmetric relationships are prevalent in real-world relationships and helps readers grasp the meanings and implications of those relationships. The results of the analyses illustrate the importance of analyzing asymmetric relationships that cannot be perceived by analysis using traditional methods, which ignore asymmetry in the data.

Researchers in behavior metrics have developed, extended, and improved methods such as multivariate statistical analysis, survey methods, cluster analysis, machine learning, multidimensional scaling, corresponding analysis or quantification theory, network analysis, clustering, factor analysis, test theory, and related factors.