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Titlebook: Methods for the Analysis of Asymmetric Proximity Data; Giuseppe Bove,Akinori Okada,Donatella Vicari Book 2021 The Editor(s) (if applicable

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發(fā)表于 2025-3-21 17:03:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Methods for the Analysis of Asymmetric Proximity Data
編輯Giuseppe Bove,Akinori Okada,Donatella Vicari
視頻videohttp://file.papertrans.cn/633/632263/632263.mp4
概述Represents a complete and up-to-date reference on methods for analyzing asymmetric proximity data.Provides a practical guide to build up graphical representation and classification of asymmetric proxi
叢書名稱Behaviormetrics: Quantitative Approaches to Human Behavior
圖書封面Titlebook: Methods for the Analysis of Asymmetric Proximity Data;  Giuseppe Bove,Akinori Okada,Donatella Vicari Book 2021 The Editor(s) (if applicable
描述.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. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relationships between pairs of objects from a given set (e.g., subjects, variables, attributes,…), collected in one or more matrices. Examples abound in many different fields such as psychology, sociology, marketing research, and linguistics and more recently several applications have appeared in technological areas including cybernetics, air traffic control, robotics, and network analysis. The capabilities of the presented algorithms are illustrated by carefully chosen examples and supported by extensive data analyses. A review of the specialized statistical software available for the applications is also provided. This monograph is highly recommended to readers who need a complete and up-to-date reference on methods for asymmetric proximity data
出版日期Book 2021
關(guān)鍵詞Data Visualization; Multidimensional Scaling; Cluster Analysis; Asymmetry; Multiway Methods; Statistical
版次1
doihttps://doi.org/10.1007/978-981-16-3172-6
isbn_softcover978-981-16-3174-0
isbn_ebook978-981-16-3172-6Series ISSN 2524-4027 Series E-ISSN 2524-4035
issn_series 2524-4027
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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沙發(fā)
發(fā)表于 2025-3-22 00:02:26 | 只看該作者
板凳
發(fā)表于 2025-3-22 02:48:37 | 只看該作者
Analysis of Symmetry and Skew-Symmetry,ods proposed to represent, separately or jointly, symmetry and skew-symmetry is presented. The relationships among the models are outlined and suggestions for strategies of data analysis are provided. Applications of the models to a real data set and a software section are provided at the end of the chapter.
地板
發(fā)表于 2025-3-22 07:12:32 | 只看該作者
Methods for Direct Representation of Asymmetry,ices are recalled, then some distance-like methods dealing with the direct representation of the asymmetric proximities are presented. The chapter ends with two applications to real data and a software section to present some programs available for models estimation.
5#
發(fā)表于 2025-3-22 12:27:45 | 只看該作者
Book 2021thods to asymmetric one-mode two-way and three-way asymmetric data. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relation
6#
發(fā)表于 2025-3-22 15:41:15 | 只看該作者
Introduction,e with respect to the methods of MDS and cluster analysis presented in the following chapters. The main types of asymmetric pairwise relationships are described, the definition of proximity and some related basic concepts are also presented. Finally, some examples of proximity data that will be analysed in the following chapters are provided.
7#
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發(fā)表于 2025-3-22 22:18:35 | 只看該作者
Methods for the Analysis of Asymmetric Proximity Data978-981-16-3172-6Series ISSN 2524-4027 Series E-ISSN 2524-4035
9#
發(fā)表于 2025-3-23 02:27:06 | 只看該作者
https://doi.org/10.1007/978-981-16-3172-6Data Visualization; Multidimensional Scaling; Cluster Analysis; Asymmetry; Multiway Methods; Statistical
10#
發(fā)表于 2025-3-23 07:08:30 | 只看該作者
Cluster Analysis for Asymmetry,hey are presented and applied to the same small illustrative data set which allows to highlight their different features and capabilities by using, when appropriate, graphical representations of the results. Attention is also paid to the issues of model selection and evaluation which are critical in applications.
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