Advanced studies in behaviormetrics and data science essays in honor of Akinori Okada /: essays in honor of Akinori Okada. (2020)
- Record Type:
- Book
- Title:
- Advanced studies in behaviormetrics and data science essays in honor of Akinori Okada /: essays in honor of Akinori Okada. (2020)
- Main Title:
- Advanced studies in behaviormetrics and data science essays in honor of Akinori Okada
- Further Information:
- Note: Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama, editors.
- Other Names:
- Imaizumi, Tadashi
Nakayama, Atsuho
Yokoyama, Satoru - Contents:
- Intro -- Foreword -- Preface -- Contents -- Contributors -- Part I Theoretically-Oriened -- Co-Clustering for Object by Variable Data Matrices -- 1 Co-Clustering -- 2 Co-clustering with Class-Specific Variances in the Variable Clusters -- 3 Clustering of Variables Around Latent Factors -- 4 Co-Clustering, Where Variable Clusters are Characterized by Class-Specific Factors -- 5 Discussion and Extensions -- References -- How to Use the Hermitian Form Model for Asymmetric MDS -- 1 Introduction -- 2 Revisit of HFM -- 3 Interpretation of the Configuration of Objects by HFM 4 Applications of HFM to Empirical Asymmetric Relational Matrices -- 5 Applications of HFM to Theoretical or Hypothetical Asymmetric Relational Data Matrices -- 6 Decomposition of ASM to Elementary ASMs via HFM -- 7 Hypothetical Force Acting on the Hilbert Space and Its Interpretation -- 8 Conclusions -- References -- Asymmetric Scaling Models for Square Contingency Tables: Points, Circles, Arrows and Odds Ratios -- 1 Introduction -- 2 Modelling of Square Contingency Tables -- 2.1 Poisson Model -- 2.2 Model Fit -- 2.3 Marginal Heterogeneity and Association -- 3 Three Distance Formulations 3.1 Distance-Radius Model -- 3.2 Slide-Vector Model -- 3.3 Symmetric Distance-Association Model -- 4 Odds Ratio Structures -- 4.1 Symmetric Distance-Association Model -- 4.2 The Distance-Radius Model -- 4.3 The Slide-Vector Model -- 5 Data Analysis -- 5.1 Symmetric Distance-Association Model -- 5.2 Distance-Radius Model -- 5.3Intro -- Foreword -- Preface -- Contents -- Contributors -- Part I Theoretically-Oriened -- Co-Clustering for Object by Variable Data Matrices -- 1 Co-Clustering -- 2 Co-clustering with Class-Specific Variances in the Variable Clusters -- 3 Clustering of Variables Around Latent Factors -- 4 Co-Clustering, Where Variable Clusters are Characterized by Class-Specific Factors -- 5 Discussion and Extensions -- References -- How to Use the Hermitian Form Model for Asymmetric MDS -- 1 Introduction -- 2 Revisit of HFM -- 3 Interpretation of the Configuration of Objects by HFM 4 Applications of HFM to Empirical Asymmetric Relational Matrices -- 5 Applications of HFM to Theoretical or Hypothetical Asymmetric Relational Data Matrices -- 6 Decomposition of ASM to Elementary ASMs via HFM -- 7 Hypothetical Force Acting on the Hilbert Space and Its Interpretation -- 8 Conclusions -- References -- Asymmetric Scaling Models for Square Contingency Tables: Points, Circles, Arrows and Odds Ratios -- 1 Introduction -- 2 Modelling of Square Contingency Tables -- 2.1 Poisson Model -- 2.2 Model Fit -- 2.3 Marginal Heterogeneity and Association -- 3 Three Distance Formulations 3.1 Distance-Radius Model -- 3.2 Slide-Vector Model -- 3.3 Symmetric Distance-Association Model -- 4 Odds Ratio Structures -- 4.1 Symmetric Distance-Association Model -- 4.2 The Distance-Radius Model -- 4.3 The Slide-Vector Model -- 5 Data Analysis -- 5.1 Symmetric Distance-Association Model -- 5.2 Distance-Radius Model -- 5.3 Slide-Vector Model -- 5.4 Models Without Main Effects -- 6 Discussion and Conclusion -- References -- Flight Passenger Behavior and Airline Fleet Assignment -- 1 Introduction -- 2 Notation -- 2.1 Airline Fleet Assignment -- 2.2 Flight Passenger Behavior -- 3 Model 4 Example -- 4.1 Starting Situation and Data -- 4.2 Results -- 5 Concluding Remarks -- References -- Comparing Partitions of the Petersen Graph -- 1 Motivation -- 2 The Automorphism Group of the Petersen Graph -- 3 Multiple Isomorphic Solutions of Graph Clustering Algorithms -- 4 Measures for Comparing Partitions and for Comparing Isomorphic Sets of Partitions -- 5 Comparing Partitions of the Petersen Graph -- 6 Summary and Outlook -- References -- Minkowski Distances and Standardisation for Clustering and Classification on High-Dimensional Data -- 1 Introduction -- 2 Distance Construction 2.1 Clustering Versus Supervised Classification -- 2.2 Standardisation -- 2.3 Boxplot Transformation -- 2.4 Aggregation -- 3 Experiments -- 3.1 Setups -- 3.2 Results -- 4 Conclusion -- References -- On Detection of the Unique Dimensions of Asymmetry in Proximity Data -- 1 Introduction -- 2 Overview of Models -- 2.1 Asymmetric Scaling -- 2.2 The Circle Model -- 2.3 Ellipse Model -- 2.4 Other Variants -- 3 Algorithm -- 4 Application -- 5 Conclusion -- References -- Multiple Regression Analysis from Data Science Perspective -- 1 Introduction -- 2 Relationship Between Variables and Type of Study … (more)
- Publisher Details:
- Singapore : Springer Singapore Pte. Limited
- Publication Date:
- 2020
- Extent:
- 1 online resource (472 p.)
- Subjects:
- 519.5
Mathematical statistics
Social sciences -- Statistical methods
Mathematical statistics
Electronic books
Electronic books - Languages:
- English
- ISBNs:
- 9789811527005
9811527008 - Related ISBNs:
- 9789811526992
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.510291
- Ingest File:
- 03_089.xml