Classification and Multivariate Analysis for Complex Data Structures
Classification and Multivariate Analysis for Complex Data Structures

Author: Bernard Fichet

Publisher: Springer Science & Business Media

Published: 2011-03-04

Total Pages: 460

ISBN-13: 3642133126

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The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.

Advanced Studies in Classification and Data Science
Advanced Studies in Classification and Data Science

Author: Tadashi Imaizumi

Publisher: Springer Nature

Published: 2020-09-25

Total Pages: 506

ISBN-13: 9811533113

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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.

Advances in Classification and Data Analysis
Advances in Classification and Data Analysis

Author: Simone Borra

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 384

ISBN-13: 3642594719

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This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica, which was held in Rome, July 5-6, 1999. From the originally submitted papers, a careful review process led to the selection of 45 papers presented in four parts as follows: CLASSIFICATION AND MULTIDIMENSIONAL SCALING Cluster analysis Discriminant analysis Proximity structures analysis and Multidimensional Scaling Genetic algorithms and neural networks MUL TIV ARIA TE DATA ANALYSIS Factorial methods Textual data analysis Regression Models for Data Analysis Nonparametric methods SPATIAL AND TIME SERIES DATA ANALYSIS Time series analysis Spatial data analysis CASE STUDIES INTERNATIONAL FEDERATION OF CLASSIFICATION SOCIETIES The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America - CSNA; Gesellschaft fUr Klassifikation - GfKI; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - CGSIS; Societe Francophone de Classification -SFC. Now the IFCS includes also the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Society -SKAD; Associayao Portuguesa de Classificayao e Analise de Dados -CLAD; Korean Classification Society -KCS; Group-at-Large.

Statistical Learning of Complex Data
Statistical Learning of Complex Data

Author: Francesca Greselin

Publisher: Springer Nature

Published: 2019-09-06

Total Pages: 201

ISBN-13: 3030211401

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This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification. It gathers selected and peer-reviewed contributions presented at the 11th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), held in Milan, Italy, on September 13–15, 2017.

Advances in Multivariate Data Analysis
Advances in Multivariate Data Analysis

Author: Hans-Hermann Bock

Publisher: Springer Science & Business Media

Published: 2012-09-30

Total Pages: 276

ISBN-13: 3642171117

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The book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology.

Multi-Dimensional Analysis
Multi-Dimensional Analysis

Author: Tony Berber Sardinha

Publisher: Bloomsbury Publishing

Published: 2019-03-21

Total Pages: 304

ISBN-13: 1350023833

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Multi-Dimensional Analysis: Research Methods and Current Issues provides a comprehensive guide both to the statistical methods in Multi-Dimensional Analysis (MDA) and its key elements, such as corpus building, tagging, and tools. The major goal is to explain the steps involved in the method so that readers may better understand this complex research framework and conduct MD research on their own. Multi-Dimensional Analysis is a method that allows the researcher to describe different registers (textual varieties defined by their social use) such as academic settings, regional discourse, social media, movies, and pop songs. Through multivariate statistical techniques, MDA identifies complementary correlation groupings of dozens of variables, including variables which belong both to the grammatical and semantic domains. Such groupings are then associated with situational variables of texts like information density, orality, and narrativity to determine linguistic constructs known as dimensions of variation, which provide a scale for the comparison of a large number of texts and registers. This book is a comprehensive research guide to MDA.

Financial Risk Management and Modeling
Financial Risk Management and Modeling

Author: Constantin Zopounidis

Publisher: Springer Nature

Published: 2021-09-13

Total Pages: 480

ISBN-13: 3030666913

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Risk is the main source of uncertainty for investors, debtholders, corporate managers and other stakeholders. For all these actors, it is vital to focus on identifying and managing risk before making decisions. The success of their businesses depends on the relevance of their decisions and consequently, on their ability to manage and deal with the different types of risk. Accordingly, the main objective of this book is to promote scientific research in the different areas of risk management, aiming at being transversal and dealing with different aspects of risk management related to corporate finance as well as market finance. Thus, this book should provide useful insights for academics as well as professionals to better understand and assess the different types of risk.

Handbook of Cluster Analysis
Handbook of Cluster Analysis

Author: Christian Hennig

Publisher: CRC Press

Published: 2015-12-16

Total Pages: 753

ISBN-13: 1466551895

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Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.The

Multivariate Data Analysis
Multivariate Data Analysis

Author: Kim H. Esbensen

Publisher: Multivariate Data Analysis

Published: 2002

Total Pages: 622

ISBN-13: 9788299333030

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"Multivariate Data Analysis - in practice adopts a practical, non-mathematical approach to multivariate data analysis. The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field. Features: Focuses on the practical application of multivariate techniques such as PCA, PCR and PLS and experimental design. Non-mathematical approach - ideal for analysts with little or no background in statistics. Step by step introduction of new concepts and techniques promotes ease of learning. Theory supported by hands-on exercises based on real-world data. A full training copy of The Unscrambler (for Windows 95, Windows NT 3.51 or later versions) including data sets for the exercises is available. Tutorial exercises based on data from real-world applications are used throughout the book to illustrate the use of the techniques introduced, providing the reader with a working knowledge of modern multivariate data analysis and experimental design. All exercises use The Unscrambler, a de facto industry standard for multivariate data analysis software packages. Multivariate Data Analysis in Practice is an excellent self-study text for scientists, chemists and engineers from all disciplines (non-statisticians) wishing to exploit the power of practical multivariate methods. It is very suitable for teaching purposes at the introductory level, and it can always be supplemented with higher level theoretical literature."Résumé de l'éditeur.

Statistical Models for Data Analysis
Statistical Models for Data Analysis

Author: Paolo Giudici

Publisher: Springer Science & Business Media

Published: 2013-07-01

Total Pages: 413

ISBN-13: 3319000322

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The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​