A Distance-based Variety of Nonlinear Multivariate Data Analysis, Including Weights for Objects and Variables PDF Download
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Author: Jacques J. F. Commandeur
Publisher:
ISBN:
Category :
Languages : en
Pages : 32
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Book Description
Author: Jacques J. F. Commandeur
Publisher:
ISBN:
Category :
Languages : en
Pages : 32
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Book Description
Author: David Kaplan
Publisher: SAGE Publications
ISBN: 1483365875
Category : Social Science
Languages : en
Pages : 529
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Book Description
Click ′Additional Materials′ for downloadable samples "The 24 chapters in this Handbook span a wide range of topics, presenting the latest quantitative developments in scaling theory, measurement, categorical data analysis, multilevel models, latent variable models, and foundational issues. Each chapter reviews the historical context for the topic and then describes current work, including illustrative examples where appropriate. The level of presentation throughout the book is detailed enough to convey genuine understanding without overwhelming the reader with technical material. Ample references are given for readers who wish to pursue topics in more detail. The book will appeal to both researchers who wish to update their knowledge of specific quantitative methods, and students who wish to have an integrated survey of state-of- the-art quantitative methods." —Roger E. Millsap, Arizona State University "This handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential reference for social science researchers as an introduction to methods and quantitative concepts of great use." —Irini Moustaki, London School of Economics, U.K. "David Kaplan and SAGE Publications are to be congratulated on the development of a new handbook on quantitative methods for the social sciences. The Handbook is more than a set of methodologies, it is a journey. This methodological journey allows the reader to experience scaling, tests and measurement, and statistical methodologies applied to categorical, multilevel, and latent variables. The journey concludes with a number of philosophical issues of interest to researchers in the social sciences. The new Handbook is a must purchase." —Neil H. Timm, University of Pittsburgh The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource. The handbook is divided into six sections: • Scaling • Testing and Measurement • Models for Categorical Data • Models for Multilevel Data • Models for Latent Variables • Foundational Issues These sections, comprising twenty-four chapters, address topics in scaling and measurement, advances in statistical modeling methodologies, and broad philosophical themes and foundational issues that transcend many of the quantitative methodologies covered in the book. The Handbook is indispensable to the teaching, study, and research of quantitative methods and will enable readers to develop a level of understanding of statistical techniques commensurate with the most recent, state-of-the-art, theoretical developments in the field. It provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method, depending on the data and distinct research situation.
Author: Sergio Zani
Publisher: Springer Science & Business Media
ISBN: 3540359788
Category : Language Arts & Disciplines
Languages : en
Pages : 420
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Book Description
This book presents new developments in data analysis, classification and multivariate statistics, and in their algorithmic implementation. The volume offers contributions to the theory of clustering and discrimination, multidimensional data analysis, data mining, and robust statistics with a special emphasis on the novel Forward Search approach. Many papers provide significant insight in a wide range of fields of application. Customer satisfaction and service evaluation are two examples of such emerging fields.
Author: Jacqueline Meulman
Publisher:
ISBN:
Category : Distance geometry
Languages : en
Pages : 222
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Book Description
Multivariate analysis and multidimensional scaling. Classification of MVA techniques: join and meet. STRIFE. STRAIN. STRESS. The majorization algorithm-model. Notation. Multivariate analysis via strife. The gifi system of nonlinear multivariate analysis. Join and meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis via join-STRIFE. Nonlinear principal components analysis via Meet-STRIFE. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Normalization. Multivariate analysis via strain. Distance properties of multivariate analysis. Join and meet. Principal components analysis. Canonical coordinates analysis. Homogeneity analysis. The asymmetric treatment of rows and columns. From classical to nonlinear multivariate analysis. Multivariate analysis via stress. From STRAIN to STRESS via multidimensional scaling. Multidimensional scaling with restrictions. Join and Meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Cone regression with a non-diagonal weight matrix. Summary of the algorithm for nonlinear canonical coordinates analysis. Some special techniques in the stress framework. Simultaneous nonlinear principal components analysis with M sets. Asymmetric treatment of sets. Nonlinear redundancy analysis. Distance driven subspace approximation. Composite nonlinear principal components analysis. The majorization algorithm for multidimensional scaling. Overview of applications. Applications of multivariate analysis via strife. Homogeneity analysis of cetacea. Nonlinear principal components analysis of the United States. Nonlinear canonical coordinates analysis of the United States. Applications of multivariate analysis via strain. Principal coordinates analysis of city crime. Principal components analysis of city crime. Canonical coordinates analysis of the Southern States. Correspondence analysis and principal coordinates analysis of the parliament. Principal components analysis and classical MDS of criminal correlations. Applications of multivariate analysis via stress. Principal coordinates analysis of the parliament. Principal coordinates analysis of the parliament via constrained MDS. Homogeneity analysis of cetacea. Classical principal components analysis of city crime. Nonlinear principal components analysis of the United States. Classical canonical coordinates analysis of the Southern State. Nonlinear canonical coordinates analysis of the United States. Nonlinear redundancy analysis of the United States. Composite nonlinear principal components analysis of the United States.
Author: Sadanori Konishi
Publisher: CRC Press
ISBN: 1466567287
Category : Mathematics
Languages : en
Pages : 340
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Book Description
Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It primarily focuses on regression modeling, classification and discrimination, dimension reduction, and clustering. The text thoroughly explains the concepts and derivations of the AIC, BIC, and related criteria and includes a wide range of practical examples of model selection and evaluation criteria. To estimate and evaluate models with a large number of predictor variables, the author presents regularization methods, including the L1 norm regularization that gives simultaneous model estimation and variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for researchers and practitioners in industrial and systems engineering, information science, life science, and other areas.
Author: Trevor F. Cox
Publisher: CRC Press
ISBN: 9781420036121
Category : Mathematics
Languages : en
Pages : 332
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Book Description
Multidimensional scaling covers a variety of statistical techniques in the area of multivariate data analysis. Geared toward dimensional reduction and graphical representation of data, it arose within the field of the behavioral sciences, but now holds techniques widely used in many disciplines. Multidimensional Scaling, Second Edition extends the popular first edition and brings it up to date. It concisely but comprehensively covers the area, summarizing the mathematical ideas behind the various techniques and illustrating the techniques with real-life examples. A computer disk containing programs and data sets accompanies the book.
Author: Michael R. Chernick
Publisher: John Wiley & Sons
ISBN: 1118211596
Category : Mathematics
Languages : en
Pages : 337
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Book Description
A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.
Author: Moody Chu
Publisher: Oxford University Press
ISBN: 0198566646
Category : Mathematics
Languages : en
Pages : 408
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Book Description
Inverse eigenvalue problems arise in a remarkable variety of applications and associated with any inverse eigenvalue problem are two fundamental questions--the theoretical issue of solvability and the practical issue of computability. Both questions are difficult and challenging. In this text, the authors discuss the fundamental questions, some known results, many applications, mathematical properties, a variety of numerical techniques, as well as several open problems.This is the first book in the authoritative Numerical Mathematics and Scientific Computation series to cover numerical linear algebra, a broad area of numerical analysis. Authored by two world-renowned researchers, the book is aimed at graduates and researchers in applied mathematics, engineering and computer science and makes an ideal graduate text.
Author: I.T. Jolliffe
Publisher: Springer Science & Business Media
ISBN: 0387224408
Category : Mathematics
Languages : en
Pages : 513
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Book Description
The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition.
Author: Joseph Hair
Publisher: Pearson Higher Ed
ISBN: 0133792684
Category : Business & Economics
Languages : en
Pages : 816
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Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
